Dependence processing method and device for multi-component project, equipment and medium

Abstract

The invention relates to the technical field of vulnerability detection, can be applied to business scenes such as financial science and technology, medical health and the like, and discloses a dependency processing method, device, equipment and medium for a multi-component project, which comprises the following steps of: analyzing description files of different component types in a multi-language project, extracting dependency data to generate unified dependency description; the method comprises the following steps: constructing a panoramic dependency graph containing component nodes and dependency edges, identifying version constraints of the component nodes to generate a unified constraint model, determining a compatible version combination by processing the constraint model, extracting a multi-component operation environment configured with a tool during installation and operation of environment configuration data, and installing project dependency according to the compatible version combination. And scanning the panoramic dependency graph based on the vulnerability information source to generate a repair instruction for updating the vulnerability component version. According to the method, centralized analysis and collaborative management of multi-language dependency are realized through unified dependency description and constraint models, and conflicts are reduced and the consistency and security of the system are improved in combination with environment configuration and a loophole repair closed-loop process.

Description

Technical Field

[0001] This invention relates to the field of vulnerability detection technology, and in particular to a method, apparatus, device, and medium for handling dependencies in multi-component projects. Background Technology

[0002] With the widespread deployment of software systems in enterprise digitalization, modern projects are generally characterized by parallel development using multiple languages, frameworks, and components. This trend is particularly evident in the fintech and healthcare sectors. Because projects often simultaneously contain Java components for business logic processing, Python scripts for data analysis and modeling, JavaScript modules for front-end presentation, and Go and Rust tools for high-performance computing or system integration, dependency management and build maintenance have become unprecedentedly complex.

[0003] In the fintech business, enterprise systems often comprise multiple subsystems, including account management, risk control decision-making, message processing, and data visualization. These subsystems are typically developed independently by different teams, using dependency management tools from their respective ecosystems, such as Maven, pip, npm, and Go Modules. Because dependency files in each language's ecosystem are completely independent, lacking a unified dependency description structure, system-level dependencies are fragmented, making it impossible to form a global dependency view. When security or compliance departments conduct component version reviews or supply chain security assessments, they often cannot directly answer the question, "Does a high-risk vulnerability in a certain underlying library affect multiple services?" Dependency governance and updates are extremely inefficient.

[0004] In the healthcare business, projects often need to handle different tasks such as image recognition, electronic medical record parsing, data visualization, and API calls within a single platform. For example, a medical image analysis module might use Python and C libraries, a data management layer might use Java or Go, and the API and front-end might use JavaScript frameworks. Each module maintains its own environment and dependencies independently, resulting in a significant disconnect between version control and build environments. Inconsistencies in dependency versions across different language ecosystems often lead to integration conflicts and even hidden errors during model deployment or data service calls. Existing dependency management technologies cannot resolve and coordinate cross-language version conflicts, limiting the repeatability and system security of healthcare data processing pipelines.

[0005] In multilingual integration projects, configuring the build and runtime environment is equally complex. Each language requires maintaining an independent virtual environment and toolchain version, and any configuration deviation can cause the system to malfunction. In high-frequency trading or clearing platforms in the financial sector, differences in the dependent environment can lead to logical misjudgments; in healthcare systems, inconsistent versions of underlying encryption or image processing libraries can result in discrepancies in diagnostic results. Existing tools lack a unified environment description and automatic configuration mechanism, making it difficult to guarantee environment consistency. Summary of the Invention

[0006] The main objective of this invention is to provide a method, apparatus, device, and storage medium for handling dependencies in multi-component projects. This aims to solve the technical problems of existing technologies being unable to uniformly model and globally parse dependency information for multi-language projects, resulting in difficulties in identifying cross-language dependency conflicts, fragmented environment configurations, and fragmented vulnerability management, thus failing to achieve integrated dependency management and security control.

[0007] To achieve the above objectives, the present invention provides a dependency handling method for multi-component projects, comprising: The project parses multiple component-specific description files corresponding to different component types, extracts dependency data from these multiple component-specific description files, and generates a unified dependency description based on the dependency data. Based on the unified dependency description, a panoramic dependency graph containing component nodes and dependency edges connecting the component nodes is constructed. Identify the version constraints of at least one component node in the panoramic dependency graph, and generate a unified constraint model based on the version constraints; By processing the unified constraint model, compatible version combinations are determined for component nodes connected by dependency edges; Environment configuration data is extracted from the unified dependency description, and the corresponding runtime and tools are installed according to the environment configuration data to configure the multi-component operating environment; Install project dependencies in the multi-component operating environment according to the compatible version combination; Based on the vulnerability information source, the component nodes in the panoramic dependency graph are scanned to identify vulnerable components, and a repair instruction is generated to modify the unified dependency description to update the version of the vulnerable component.

[0008] Furthermore, to achieve the above objectives, the present invention provides a dependency processing apparatus for multi-component projects, comprising: The dependency modeling module is used to parse multiple component-specific description files in the project that correspond to different component types, extract dependency data from the multiple component-specific description files, and generate a unified dependency description based on the dependency data; The graph construction module is used to construct a panoramic dependency graph containing component nodes and dependency edges connecting the component nodes based on the unified dependency description. The constraint modeling module is used to identify the version constraints of at least one component node in the panoramic dependency graph and generate a unified constraint model based on the version constraints. A compatibility solving module is used to determine compatible version combinations for component nodes connected by dependency edges by processing the unified constraint model; The environment configuration module is used to extract environment configuration data from the unified dependency description and install the corresponding runtime and tools according to the environment configuration data to configure the multi-component operating environment. A dependency deployment module is used to install project dependencies in the multi-component operating environment according to the compatible version combination; The vulnerability remediation module is used to scan the component nodes in the panoramic dependency graph based on the vulnerability information source to identify components with vulnerabilities, and generate remediation instructions for modifying the unified dependency description to update the version of the component with vulnerabilities.

[0009] Furthermore, to achieve the above objectives, the present invention also provides a computer device, the computer device including a memory, a processor, and a dependency processing program for a multi-component project stored in the memory and executable on the processor, wherein when the dependency processing program for the multi-component project is executed by the processor, it implements the steps of the dependency processing method for the multi-component project as described above.

[0010] Furthermore, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a dependency handling program for a multi-component project, wherein the dependency handling program for the multi-component project, when executed by a processor, implements the steps of the dependency handling method for the multi-component project as described above.

[0011] Beneficial Effects: This invention relates to the field of vulnerability detection technology and can be applied to business scenarios such as fintech and healthcare. It discloses a method, apparatus, device, and medium for dependency processing in multi-component projects, including: parsing description files of different component types in a multi-language project; extracting dependency data to generate a unified dependency description; constructing a panoramic dependency graph containing component nodes and dependency edges; identifying version constraints of component nodes and generating a unified constraint model; determining compatible version combinations by processing the constraint model; extracting environment configuration data to install corresponding runtimes and tools to configure the multi-component operating environment; installing project dependencies in this environment according to compatible version combinations; and generating repair instructions for updating vulnerable component versions based on vulnerability information source scanning of the panoramic dependency graph. This invention, by introducing a unified dependency description and a unified constraint model into multi-language projects, achieves centralized parsing and collaborative management of cross-language dependency information. Combined with environment configuration and vulnerability repair mechanisms, it forms a complete closed loop from dependency modeling to environment construction to security governance, thereby reducing cross-language dependency conflicts, improving environment consistency, and significantly enhancing the security and controllability of multi-component systems. Attached Figure Description

[0012] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a schematic diagram of an application environment for a dependency handling method for multi-component projects according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating an embodiment of the dependency handling method for multi-component projects according to the present invention; Figure 3 This is a schematic diagram of the functional modules of a preferred embodiment of the dependency processing device for multi-component projects of the present invention; Figure 4 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention; Figure 5 This is another structural schematic diagram of a computer device according to one embodiment of the present invention. Detailed Implementation

[0013] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0014] The dependency handling method for multi-component projects provided in this embodiment of the invention can be applied to, for example... Figure 1In this application environment, the client communicates with the server via a network. The server can parse description files of different component types in a multi-language project through the client, extract dependency data to generate a unified dependency description, construct a panoramic dependency graph containing component nodes and dependency edges, identify version constraints of component nodes and generate a unified constraint model, determine compatible version combinations by processing the constraint model, extract environment configuration data to install the corresponding runtime and tools to configure the multi-component operating environment, install project dependencies in this environment according to the compatible version combinations, and generate repair instructions for updating vulnerable component versions based on vulnerability information source scanning of the panoramic dependency graph. This invention, by introducing a unified dependency description and a unified constraint model into a multi-language project, achieves centralized parsing and collaborative management of cross-language dependency information. Combined with environment configuration and vulnerability repair mechanisms, it forms a complete closed loop from dependency modeling to environment construction to security governance, thereby reducing cross-language dependency conflicts, improving environment consistency, and significantly enhancing the security and controllability of multi-component systems. The client can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a standalone server or a server cluster consisting of multiple servers. The invention will be described in detail below through specific embodiments.

[0015] Please see Figure 2 , Figure 2 This is a flowchart illustrating an embodiment of the dependency handling method for multi-component projects provided by the present invention. It should be noted that although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0016] like Figure 2 As shown, the dependency handling method for multi-component projects proposed in this invention includes the following steps: S10, parse multiple component-specific description files in the project that correspond to different component types, extract dependency data from the multiple component-specific description files, and generate a unified dependency description based on the dependency data; In this embodiment, when parsing description files corresponding to different component types in the project, an adaptation mechanism needs to be established to address the differences in file structure and syntax across various language ecosystems. Description files for different component types have their own independent formats and dependency semantics. For example, Maven in the Java ecosystem uses XML structures to define dependencies and version constraints, npm in the JavaScript ecosystem organizes package names and semantic versioning rules using JSON structures, Python uses text-based requirements files, and Go typically defines dependencies using module declarations and hash verification information. To enable the system to understand these heterogeneous file contents, a set of parser adaptation modules needs to be established. Each adaptation module is designed for a specific file type and possesses capabilities for syntax tree construction, key field extraction, dependency resolution, and exception handling. During the parsing process, the system reads the file into an abstract grammatical representation and extracts component identifiers, version numbers, dependency types, and optional source information through rule mapping.

[0017] The process of extracting dependency data from these component-specific description files includes not only field extraction but also format conversion and semantic unification. The extracted dependency data typically includes package name, version number, scope (e.g., compile-time or runtime), optional dependencies, conflict rules, and image repository paths. After collecting the dependency data, the system performs structured mapping based on a predefined metadata model, transforming dependency elements from different languages ​​into component objects and dependency relationship objects in a unified structure. This mapping process uses a hash index mechanism to ensure the generation of unique identifiers, preventing duplicate dependencies across languages ​​from being identified as different objects.

[0018] When generating a unified dependency description based on extracted dependency data, the system organizes all component objects and dependency relationship objects into a serializable unified description structure. This structure can adopt a hierarchical nested encoding form, containing global information about project objects (such as project name, version, and language list) and a collection of component objects. Component objects record their identifiers, version constraints, and identifiers of other components they depend on, thereby establishing cross-language dependency chains in the unified description file. To ensure the traceability and integrity of the description file, the system adds a verification digest, generation timestamp, and language compatibility identifier fields during the generation process. The generated unified dependency description will be stored in a database or configuration repository for subsequent dependency analysis and environment building.

[0019] This embodiment achieves cross-language integration and standardized representation of dependencies by uniformly parsing and extracting dependency data from description files of different component types in multilingual projects, eliminating dependency silos. The unified dependency description enables the system to trace dependency chains globally, providing a consistent structural foundation for subsequent dependency conflict analysis, version constraint resolution, and vulnerability scanning, thereby improving dependency management efficiency and reducing maintenance complexity.

[0020] S20, Based on the unified dependency description, construct a panoramic dependency graph containing component nodes and dependency edges connecting the component nodes; In this embodiment, constructing a panoramic dependency graph containing component nodes and dependency edges based on a unified dependency description requires first parsing the data structure in the unified dependency description to extract component objects and dependency relationship objects. The unified dependency description is typically stored in a hierarchical structure, where component objects define the component's unique identifier, language type, version information, and dependency list, while dependency relationship objects describe the reference relationships and constraint attributes between components. The parsing process is completed by the dependency resolution module, which maps the description data into dependency graph objects in memory through abstract syntax tree traversal or structured query language parsing. Each component object is instantiated as a node element in the graph, containing a component identifier, version number, language attribute, and metadata; each dependency relationship object is instantiated as an edge element connecting two nodes, with attributes such as dependency direction, dependency scope, and constraint conditions attached to the edge.

[0021] During the dependency graph construction process, the system performs integrity checks and redundancy resolution on dependencies. Integrity checks are performed by verifying whether the node pointed to by the dependency edge exists in the component set. If a missing node is found, a placeholder node is automatically created and its source is marked as an external dependency. Redundancy resolution identifies and merges duplicate dependencies through hash comparison or a unique index mechanism. To prevent circular dependencies from causing abnormal graph structure, the system uses topological sorting to detect cycles. Once a cycle is detected, it is resolved into a computable directed acyclic graph by splitting nodes or adjusting dependency paths.

[0022] After generating the comprehensive dependency graph, semantic expansion of the dependency relationships is required. The system supplements implicit dependency information based on specific characteristics of the language ecosystem. For example, in Java, it resolves the parent POM inheritance chain; in Python, it analyzes the dependency import hierarchy in the requirements file; and in JavaScript, it tracks the peerDependencies relationship in npm. Ultimately, the dependency graph includes not only explicit dependency edges but also derived and transitive dependencies, thus achieving a comprehensive model of the overall dependency structure of the project.

[0023] To support subsequent visualization and query analysis, the dependency graph is mapped and stored in a graph database. Each component node is tagged with a unique ID, language label, and version attribute in the database, and dependency edges are stored as weighted directed edges. Weights can be calculated based on dependency strength, call level, or update frequency for subsequent dependency path analysis and impact assessment. This graph database supports graph query languages ​​such as Cypher and Gremlin, facilitating cross-language dependency tracking and version conflict diagnosis.

[0024] This embodiment constructs a panoramic dependency graph based on a unified dependency description, achieving structured modeling of cross-language components and global visualization of dependency relationships. This mechanism accurately reflects the dependency chains between components in a project, providing a unified data foundation for version conflict detection, vulnerability propagation analysis, and dependency impact assessment, thereby improving dependency governance efficiency and system stability.

[0025] S30, identify the version constraints of at least one component node in the panoramic dependency graph, and generate a unified constraint model based on the version constraints; In this embodiment, identifying version constraints of component nodes in the panoramic dependency graph aims to extract version restriction information for each component from the dependency network and establish a unified constraint expression structure across languages ​​and dependency sources. Each component node in the panoramic dependency graph typically carries version constraints from its original description file, such as fixed version, range version, upper and lower bound constraints, or logical composite constraints. For example, in Java's Maven ecosystem, the common version constraint [1.0, 2.0) represents a range greater than or equal to 1.0 and less than 2.0; in npm, ^3.2.1 indicates compatibility with 3.xx versions; and in Python, >= 1.5, < 2.0 indicates constraints with both upper and lower bounds. Since different language ecosystems have different semantic parsing methods, the unified constraint model needs to provide a universal constraint expression structure across languages.

[0026] In the implementation process, the system first traverses all component nodes in the panoramic dependency graph, reading the version constraint field by accessing the node's attribute set. For nodes without explicit version constraints, the system derives implicit constraints based on the dependency propagation chain, ensuring the integrity of constraint information. Each extracted version constraint is encapsulated into an intermediate expression unit, containing a component identifier, the original constraint expression, the language type, and the semantic rule type. Subsequently, the system inputs these intermediate expression units into the constraint translation module, which transforms them into a unified constraint syntax based on the version syntax definitions of different languages. For example, it unifies npm's semantic versioning rules and Maven's scope expressions into a structure form with upper bound, lower bound, and optional open / closed intervals.

[0027] The process of generating a unified constraint model is not merely syntactic transformation, but also structured modeling. The unified constraint model consists of three types of objects: component identifier objects, version constraint objects, and constraint relationship objects. Component identifier objects uniquely represent component entities in the project; version constraint objects record the allowed version range, priority, conflict flags, and constraint sources for the component; constraint relationship objects describe the dependencies, transitive constraints, and exclusion rules between components. When building the model, the system maps these objects to a persistent structural graph for subsequent constraint solving, conflict detection, and version composition analysis.

[0028] During the constraint model generation process, the system also performs constraint conflict detection. By analyzing the intersection relationships between constraint objects of multiple versions, it can identify cases of version overlap or incompatibility. For example, when component A depends on component B with version < 2.0, while component C depends on component B with version >= 2.1 through another link, the two will be marked as conflicting in the unified model. The system uses a conflict marking mechanism to add a unique identifier to each set of conflicting constraints and writes the results into the unified constraint model, providing input for the subsequent constraint solving stage.

[0029] The resulting unified constraint model is stored in the form of structured data, which can be used for visualization and cross-language dependency decision-making. The model not only supports static queries but can also be dynamically refreshed with version updates, ensuring that the system can reflect changes in dependency constraints in real time.

[0030] This embodiment achieves standardized expression and centralized governance of cross-language dependency constraints by identifying version constraints of component nodes in the panoramic dependency graph and establishing a unified constraint model. This mechanism eliminates conflicts caused by version semantic inconsistencies between different language ecosystems, provides unified input for version resolution and compatibility analysis, and thus improves the accuracy of dependency consistency and version decisions.

[0031] S40, by processing the unified constraint model, determine compatible version combinations for component nodes connected by dependency edges; In this embodiment, determining compatible version combinations for component nodes connected by dependent edges by processing the unified constraint model is a process of constraint solving and conflict coordination within the global dependency graph. The unified constraint model records the version range, constraint relationships, and conflict marker information for each component. To generate compatible version combinations, the system needs to find a set of feasible version solutions that satisfy all dependency conditions within the model's constraint space. This process is executed by the constraint solving module, which takes the unified constraint model as input, parses the component identifier objects, version constraint objects, and constraint relationship objects within it, constructs a constraint representation matrix, and performs compatibility calculations using a constraint solving algorithm.

[0032] The first stage of constraint solving is satisfiability analysis. The system transforms version constraint objects into logical constraint expressions, such as "Component A version ≥ 1.0 and < 2.0" and "Component B version is compatible with version A," and establishes a Boolean solution model. The constraint solving module can use the CSP (Constraint Satisfaction Problem) or SAT (Boolean Satisfiability) algorithm to solve the problem, progressively traversing the version space to determine combinations that satisfy all constraints. If all constraints have an intersection, a feasible solution is obtained.

[0033] When the solver detects constraint conflicts, the system performs a conflict extraction process. By tracing the constraints in the solution path that lead to unsatisfiability, the system extracts a set of key constraints and identifies contradictory version boundaries. Subsequently, the system enters the tuning phase, generating several tuning schemes based on a predefined solution mechanism library. These schemes may include relaxing specific constraint boundaries, selecting approximate versions, or replacing compatible dependencies. For each scheme, the system calculates the tuned model consistency score and constraint satisfaction, and selects the highest priority scheme to apply to the model, generating a tuned unified constraint model.

[0034] The updated unified constraint model is input into the constraint solving module again for a second solution to obtain a new compatible version combination. If the solution is successful again, the system marks the version combination as a compatible version combination and records the version source, dependency path, and conflict resolution process for subsequent dependency installation and version tracking.

[0035] In some implementations, the constraint solving module also analyzes the topological order of dependent edges to ensure consistency of the solution results in the dependency transitive chain. Through hierarchical processing of dependent edges, the system can prioritize resolving version constraints of upstream components, thereby reducing conflict propagation in subsequent transitive dependencies.

[0036] This embodiment achieves version compatibility analysis and automatic resolution under cross-language dependencies by processing and solving a unified constraint model. This mechanism can coordinate dependency conflicts between different language ecosystems and automatically generate feasible version combinations, thereby reducing the complexity of manual investigation and adjustment, and improving the accuracy of dependency resolution and the stability of project construction.

[0037] S50, extract environment configuration data from the unified dependency description, and install the corresponding runtime and tools according to the environment configuration data to configure the multi-component operating environment; In this embodiment, extracting environment configuration data from the unified dependency description and installing runtime and tools accordingly to configure the multi-component operating environment is a crucial step in establishing a consistent execution foundation for cross-language projects after version compatibility is resolved. The unified dependency description typically records the project's global dependency information in a standardized structure (such as JSON, YAML, TOML, etc.), including not only libraries and modules but also configuration items such as runtime environment, language version, compiler, build tools, and plugins. The core objective of this step is to automatically identify and uniformly configure the environment dependencies required by each component in a multi-language, multi-framework project, thereby forming a complete and runnable multi-component operating environment.

[0038] The system first parses the unified dependency description file, extracting environment-related fields. These fields typically include language type (e.g., Python, Java, Node.js, Go), runtime version number, build tool type (e.g., Gradle, npm, pip, go mod), dependency manager configuration (e.g., source address, authentication credentials), system library dependencies, and operating system compatibility requirements. The extracted environment configuration data undergoes semantic mapping processing, transforming it into standardized environment description objects. Each description object corresponds to a component environment unit, recording metadata such as runtime, compilation tools, and dependency installation methods.

[0039] To ensure consistency across multi-component environments, the system performs environment conflict detection after extraction. By analyzing the runtime versions, system library dependencies, and toolchain versions of different components, potential conflicting combinations are identified. For example, if one component requires Python 3.8 and another requires Python 3.11, the system will mark the version conflict during conflict detection and determine a coexistence solution (such as virtual environment isolation or containerized configuration) using a version mapping table.

[0040] The system then enters the environment installation phase. Based on the standardized environment description object, it sequentially calls the runtime installation modules for the corresponding language. For example, in a Linux environment, the system automatically installs Python, JDK, or Node.js using a package management tool, and loads the appropriate dependency manager based on the component type. For Java components, it installs Maven or Gradle; for Python components, it installs pip and virtual environments; for Node.js components, it installs npm or yarn; and for Go components, it sets GOPATH and the dependency cache path.

[0041] The system performs batch installation operations through automated scripts or containerized configurations (such as Dockerfiles or Podman templates). In containerized scenarios, the system can generate multi-stage build images based on a unified dependency description, with each stage corresponding to a component runtime environment, and integrate cross-component runtime support in the final image. For non-containerized environments, the system adopts a virtual environment directory isolation strategy, allocating runtimes and dependent tools of different languages ​​to independent logical spaces to achieve version isolation and unified scheduling.

[0042] After installation, the system performs environment verification. This involves calling version detection commands and dependency integrity checks of each component to verify that the installation results match the environment configuration data. Upon successful verification, the system generates a configuration index for the multi-component operating environment, recording information such as runtime paths, tool versions, and dependency source configurations for use by subsequent dependency installation and vulnerability scanning modules.

[0043] In one implementation, the system employs a modular environment configuration engine. This engine registers independent environment management plugins for each language type based on environment configuration data output by a unified dependency description resolver. Each plugin encapsulates runtime installation logic, dependency source configuration logic, and environment variable setting logic. For example, the Python plugin is responsible for installing a specified version of the Python interpreter, pip manager, and virtual environment, and generating a .venv environment in the project root directory; the Node.js plugin is responsible for installing the Node.js version and npm, and updating the package-lock.json lock file to ensure dependency consistency.

[0044] In another implementation, the system automates environment configuration through container image building. The parsed environment configuration data is used to generate container image build scripts. The system can determine the build order based on the component dependency topology, prioritizing the construction of the basic runtime layer (such as JDK and Python), then the tool layer (such as Maven, pip, and npm), and finally generating a multi-component runtime layer, thereby forming a reusable cross-language operating environment.

[0045] In distributed projects, the system can employ a remote environment distribution mechanism. The environment configuration module pushes the generated environment description object to remote build nodes, where automatic installation and verification are performed. In a distributed environment, the system supports a caching mechanism, allowing duplicate projects to directly load cached images, thereby significantly reducing build time.

[0046] This embodiment achieves unified construction and deployment of cross-language project environments by extracting environment configuration data from a unified dependency description and automatically installing the corresponding runtime and tools. This mechanism eliminates problems such as version inconsistencies, tool conflicts, and duplicate installations inherent in traditional manual configuration, enabling projects to maintain a consistent dependency baseline across multi-component environments. This invention, through an automated and structured environment configuration process, achieves reproducibility and portability of the multi-language dependency management system, thereby improving system integration efficiency and operational stability.

[0047] S60, Install project dependencies in the multi-component operating environment according to the compatible version combination; In this embodiment, installing project dependencies in a multi-component operating environment based on compatible version combinations is a crucial step in achieving project consistency and dependency reproducibility. After solving the unified constraint model, the system obtains a set of compatible version combinations, which clearly defines the required dependency versions and dependencies of all components in the project. Based on this, the system needs to perform dependency installation operations in the configured multi-component operating environment to ensure that each component loads the correct dependency libraries and tools at runtime.

[0048] The system first reads the dependency manifest information recorded in the compatible version combinations. Each dependency manifest entry includes a component identifier, dependency package name, version number, dependency type (e.g., development dependency, runtime dependency, test dependency), and source path. The system automatically matches the appropriate dependency management tool module based on the component's language or runtime type. For example, a Python component uses the pip module to install dependencies, a Java component uses Maven or Gradle to parse the pom file or build script, a Node.js component uses npm or yarn to install packages, and a Go component downloads dependencies using the `go mod` command.

[0049] During installation, the system performs topological sorting of dependency installation order. Based on the dependency edge relationships between components in the panoramic dependency graph, the system determines the directed acyclic sequence of dependency installation, prioritizing the installation of basic components without dependent nodes, followed by higher-level components, to avoid installation failures caused by missing dependencies or circular references. If a dependency version is detected to be incompatible with the runtime during installation, the system will invoke the compatibility verification module to replace or downgrade the dependency and update the record of compatible version combinations to ensure that the final installation result is consistent with the environment configuration.

[0050] The system supports a multi-language dependency isolation mechanism. For components with runtime differences, the system creates independent virtual spaces or container sublayers in the multi-component operating environment to prevent dependency conflicts. Python component dependencies are installed and executed in the virtual environment directory, Node.js components are installed in a separate node_modules directory, and Java component dependencies are isolated through local repository paths, ensuring that each component is logically independent but can run collaboratively at the system level.

[0051] After dependency installation is complete, the system performs dependency verification for each component. The verification module verifies the completeness of the installation results and their compliance with version combination constraints by calling language-level tool check commands (such as pip check, mvn dependency:tree, npm audit). It also records installation logs and dependency lock files for subsequent version backtracking and reproducibility.

[0052] In one implementation, the system uses a unified dependency scheduling engine to manage cross-language dependency installation tasks. This engine takes compatible version combinations as input and generates a queue of dependency installation tasks, with each queue item corresponding to the installation task of a language component. The scheduling engine determines execution priorities based on the hierarchy of the dependency graph and executes installation instructions through a parallel thread pool, thereby reducing the overall installation time.

[0053] In another implementation, the system automates dependency installation by building containerized images. After resolving compatible version combinations, the system generates an independent image build layer for each component, executes dependency installation commands, and generates a cache layer. Finally, all component image layers are merged in a multi-component operating environment to generate a unified runtime image, achieving complete consistency and portability of the environment and dependencies.

[0054] In a continuous integration environment, the system supports an incremental dependency update mechanism. When a dependency in a version combination is updated, only the affected components are reinstalled, while other components continue to use cached dependencies, thereby improving installation efficiency and reducing build time.

[0055] This embodiment achieves integrated installation and precise control of cross-language dependencies by installing project dependencies in a multi-component operating environment based on compatible version combinations. It ensures that each component loads its compatible dependency versions, avoiding version conflicts and environment inconsistencies, and significantly improving build reliability and runtime stability.

[0056] S70, based on the vulnerability information source, scan the component nodes in the panoramic dependency graph to identify the components with vulnerabilities, and generate a repair instruction for modifying the unified dependency description to update the version of the component with the vulnerability.

[0057] In this embodiment, identifying vulnerable components by scanning component nodes in the panoramic dependency graph based on vulnerability information sources and generating remediation instructions to modify the unified dependency description to update the versions of vulnerable components is a crucial step in achieving automated security dependency governance. This process begins after dependency installation is complete. The system performs a full comparison of project dependencies and dynamically generates remediation instructions by accessing multi-source vulnerability databases. Vulnerability information sources may include national information security vulnerability databases (CNVD, CVE), open-source vulnerability databases (such as NVD, OSV), and enterprise internal security knowledge bases. These sources provide data such as vulnerability ID, affected components, affected version range, vulnerability level, and recommended remediation versions.

[0058] The system first parses the comprehensive dependency graph, extracting the unique identifier, version information, and dependencies of each component node. For each component node, the system accesses vulnerability information sources using component name and version as search criteria. The retrieval process employs a parallel query mechanism to improve detection efficiency. The system performs structured parsing of the query results to construct a vulnerability matching result set. The matching rules are based on component identifier, version range, and vulnerability description keywords. Version matching uses a range judgment logic; if the component version falls within the vulnerability's impact range, it is marked as having a vulnerability.

[0059] After identifying vulnerable component nodes, the system performs vulnerability impact analysis. This analysis considers not only the direct vulnerability risk of a single component but also assesses the potential indirect impact along its dependency paths. For example, if upstream component A depends on component B and component B contains a vulnerability, the system will mark component A as an affected node so that it can be updated synchronously in subsequent fixes. The system identifies all affected paths using a hierarchical traversal algorithm of the dependency graph, forming a vulnerability propagation chain.

[0060] After vulnerability identification and analysis, the system enters the remediation instruction generation phase. Based on the remediation suggestions provided by the vulnerability information source, the system searches for the security version or alternative version number of the corresponding component. If no specific remediation version is provided in the vulnerability information source, the system can select the most recent security version or minor version branch through a version stability scoring mechanism. The remediation instructions are generated in a structured format, including the operation type (version update, dependency replacement, or patch upgrade), component identifier, target version, and modification location (path in the unified dependency description file).

[0061] The generated remediation instructions are applied to the unified dependency description through the dependency description editing module, updating the version number or reference path of the affected components. The system records a revision log for each remediation operation, including the vulnerability number, original version, remediation version, execution time, and remediation result status, to support subsequent compliance audits and backtracking analysis.

[0062] In one implementation, the system employs a local caching and remote vulnerability source synchronization mechanism. Vulnerability information sources are updated to the local database via scheduled tasks, and scanning tasks perform matching queries based on the local cache, thereby reducing latency caused by external network requests. The scanning engine uses hash indexes to quickly locate component names and combines them with a version range mapping table for efficient comparison.

[0063] In another implementation, the system integrates a machine learning vulnerability matching model. The model is trained on historical vulnerability samples and automatically identifies component vulnerabilities involving name variants, renamed libraries, or non-standard version numbers through semantic similarity calculations. For example, when a project uses modified component names or private images, the model can determine whether it corresponds to a publicly disclosed vulnerable component based on similarity, thus improving detection coverage.

[0064] In enterprise-level projects, the system can also be integrated with CI / CD processes. A vulnerability scan is automatically triggered before each build; when a new vulnerability is discovered, a fix is ​​immediately generated and the release process is halted until the vulnerability is fixed, at which point subsequent deployments are executed. This mechanism ensures that dependencies running in the production environment are always in a secure version.

[0065] This embodiment achieves real-time identification and intelligent remediation of dependency security issues by scanning a panoramic dependency map based on vulnerability information sources and automatically generating remediation instructions. The system can quickly identify potential security risks in complex projects with multiple languages ​​and components, automatically generate and apply remediation strategies, thereby significantly reducing manual security maintenance costs and lowering the system's attack surface caused by component vulnerabilities. Through synchronized updates with the unified dependency description, project dependencies always maintain the latest security status, ensuring system security and continuous availability.

[0066] In one embodiment, step S10 above includes: S101, Define a metadata model for a unified dependency description language, wherein the metadata model includes project objects, component objects, and dependency objects; S102, Configure a parser adapter for each component type that can understand the syntax structure of the native description file of the corresponding component type; S103, using the resolver adapter configured for each component type, read and parse multiple component-specific description files in the project corresponding to different component types, and extract dependency data containing component identifiers and version constraints from the multiple component-specific description files; S104, The dependency data is mapped and converted into a unified dependency description language format according to the metadata model to generate a unified dependency description; S105, the unified dependency description is stored in the graph database to convert the component object into a graph node in the graph database and the dependency object into a graph edge in the graph database.

[0067] In this embodiment, a unified dependency description language metadata model is used to extract scattered dependency information from multi-language ecosystems into a consistent data structure. The model contains three basic objects: a project object to carry project-level metadata and global configuration, including fields such as project identifier, version baseline, language list, dependency source list, signature, and verification digest; a component object to abstract a single reusable unit, including component identifier, language type, source type (artifact repository, version control repository, local module), version information, scope division (build phase, runtime phase, test phase), optional dependency tags, platform restrictions, and license fingerprint; and a dependency relationship object to describe the reference relationship between two component objects, including the referenced identifier, version constraint expression, dependency direction, transitivity tag, exclusion list, and source tracing chain. The model fields use an extensible key space, reserving namespaces and additional tags to facilitate the introduction of new ecosystems and attributes later. To meet the needs of cross-team collaboration and auditing, the model requires fields to have a deterministic serialization order, stable key names, and type validation rules, while also recording generation time and source path to support traceability.

[0068] The parser adapter is a bridging component connecting heterogeneous description files with a unified model. One adapter is configured for each component type, and each adapter possesses four capabilities: input detection, structure parsing, semantic interpretation, and anomaly recovery. Input detection identifies file type and encoding; structure parsing maps XML, JSON, TOML, INI, or line-based text to an abstract grammatical representation; semantic interpretation extracts key elements such as component identifiers, version constraints, scope, and origin; and anomaly recovery implements fault tolerance strategies for missing fields, comment contamination, or unclosed inline quotes. Adapters are assembled as plugins, supporting loading by language and ecosystem, and have versioned configuration and canary release capabilities. To reduce parsing bias caused by differences between ecosystems, a standardized dictionary and mapping table are introduced, aligning synonymous fields to a unified key (e.g., groupId and namespace are unified to namespace, artifactId and package name are unified to name). All adapters output a consistent set of intermediate objects, containing candidate component objects and candidate dependency objects, along with source location information and a verification digest.

[0069] When reading and parsing various component-specific description files, three types of structures need to be covered: single-repository multi-module, single-repository multi-language, and cross-repository aggregation. Single-repository multi-module uses a root directory aggregator to scan subdirectory lists, identifying module boundaries and inheritance relationships. Single-repository multi-language uses a language detector to discover manifest files and lock files for different ecosystems and allocates a parsing queue for each ecosystem. Cross-repository aggregation uses the input manifest index or manifest repository list, employing parallel fetching and caching mechanisms to batch retrieve description files and reference locks. During the parsing phase, component identifiers are normalized, synthesized into unique identifiers, and namespaces, names, and source domains are concatenated. Fingerprint hashing is introduced when necessary to avoid name conflicts across ecosystems. Version constraints are unified into five basic components: upper bound, lower bound, open / closed intervals, compatibility semantics, and exclusion sets. Both line-based and symbolic expressions are mapped to this combined structure. When processing derivation relationships, the parser completes implicit dependencies, such as parent POM inheritance, peer dependencies, and optional dependency triggering conditions, and records the triggering conditions as attributes in the dependency object.

[0070] The process of mapping and encoding dependency data into a unified dependency description language format includes four stages: field alignment, conflict merging, semantic normalization, and order stabilization. Field alignment corrects key names and types based on the metadata model; conflict merging merges source and version constraints when the same component identifier appears multiple times, using source priority and timestamps for resolution, and retaining conflict markers for subsequent solving; semantic normalization folds the semantics of multiple ecosystem versions into a unified range and compatible bit set, maintaining comparability and derivability; order stabilization eliminates non-deterministic differences through key sorting and list sorting, outputting consistent serialized text in any environment. The encoding format supports both JSON and YAML representations, with strict field and hierarchy alignment for easy switching between different toolchains. During the generation stage, generation fingerprints and source hashes are written to establish content addressing capabilities, ensuring that any subsequent changes can be accurately identified through hash changes.

[0071] When storing unified dependency descriptions in a graph database, component objects are mapped to graph nodes, and dependency relationship objects are mapped to graph edges. The minimum set of attributes for a node includes a unique identifier, language, version set, license digest, and source domain; the set of attributes for an edge includes a target identifier, version constraint range, transitivity, scope, exclusion list, and source path. The write process employs transactional semantics and an idempotent write strategy: if the same identifier exists, an update is performed and a snapshot of the historical version is retained; if it does not exist, a new node is created. Dependency edges are deduplicated using composite keys to avoid duplicate relationships. To support efficient retrieval, indexes are created on the node's unique identifier, language, and name; composite indexes are created on the edge's target identifier and version constraint fields. To support impact analysis and path lookup, in-degree and out-degree count caches are added to nodes. The storage layer records a time-version chain, allowing unified dependency descriptions to be replayed at specific points in time, and supports auditing and rollback. To adapt to ultra-large-scale graphs, sharding and replication configurations are provided; edge writes are batched; node attributes are stored in a columnar manner to reduce IO pressure; and cross-datacenter deployments maintain eventual consistency through asynchronous replication.

[0072] Component identifiers originate from sources including artifact coordinates, package registry namespaces, remote paths from source code repositories, and mirror repository tags. When multiple sources coexist, the parser creates an equivalence mapping table, where any identifier in the equivalence set can point to the same node. Version constraints originate from sources including explicit constraints in manifest files, lock file records, inheritance chains, and parser derivation. Source fields are integrated into dependency objects, facilitating the tracking of constraint causes and subsequent solution bases. Warnings generated during the mapping process are categorized into three types: missing, ambiguous, and conflicting. Missing indicates that the component failed to resolve to a version or source; ambiguity indicates that components with the same name from different sources cannot be determined to be equivalent; and conflicting indicates that the same component is assigned incompatible constraints. All warnings are entered into a unified log and recorded with tags in the graph for use in subsequent processing stages.

[0073] This embodiment extracts heterogeneous description files from a multilingual ecosystem into a consistent data representation through a unified dependency description. The parser adapter isolates structural and semantic differences at a boundary layer, and the graph database solidifies component objects and dependency objects into a queryable and replayable global view. Through standardized component identifiers and comparable version constraints, cross-language dependencies can be compared, merged, and tracked within the same semantic space. Through deterministic encoding and idempotent database storage, the unified description generated in any environment and at any point in time remains consistent. Through indexing and time-version chains, subsequent conflict identification, version combination solutions, environment construction, and vulnerability propagation analysis obtain stable input.

[0074] In one embodiment, step S20 above includes: S201, Based on the component objects and dependency relationship objects in the unified dependency description, construct an in-memory dependency graph object, wherein the dependency graph object consists of component nodes representing components and dependency edges representing dependencies; S202, detect the circular dependencies in the dependency graph object, parse the detected circular dependencies, and generate a parsed dependency graph object; S203, perform dependency analysis on the parsed dependency graph object to obtain dependency path analysis results and isolated component node analysis results; S204, associate the dependency path analysis results and the isolated component node analysis results with the parsed dependency graph object to generate a panoramic dependency graph for visualization analysis; S205, providing a visual interactive interface for the panoramic dependency map.

[0075] In this embodiment, the unified dependency description provides structured entries for component objects and dependency objects. First, a dependency graph object is created in memory, establishing three basic containers: a component index table for quickly locating node instances by component identifier, an outgoing edge adjacency table recording the set of dependency edges pointing from one component to a downstream component, and an incoming edge adjacency table recording upstream sources. Component node instances include component identifier, language type, version information, scope marker, license summary, and source path; dependency edge instances include start-point identifier, end-point identifier, version constraint expression, transitivity marker, exclusion list, and source path. During creation, a consistency check is performed on each dependency object. If the end point does not appear in the component index table, a placeholder node is generated and marked with an external source; if multiple semantically equivalent dependency entries exist for the same start and end point, they are merged into a single dependency edge, and the source and marker are combined. To avoid key conflicts, component identifiers are constructed using a namespace and name concatenation supplemented with fingerprint hashing, and are incorporated into a unique key space; all nodes and edges are accompanied by a generation time and content summary for easy subsequent backtracking.

[0076] Cyclic dependency detection takes a memory dependency graph object as input and identifies back edges using a three-color access status and backtracking path recording method. When a back edge is encountered during access, it is immediately written to the cycle group buffer, recording the participating components and edge sequence, and marking the cycle group number to the relevant node and edge. After detection, the parsing process begins, providing two parsing methods: First, the cycle group is converged into agglomerative nodes, retaining inbound and outbound edges, and the edges inside the cycle are included as in-group details; Second, the original nodes remain unchanged, only adding cycle markers to the cycle edges and splitting out an acyclic alternative path for subsequent analysis. One of the two methods is selected for output according to configuration. The output result is defined as the parsed dependency graph object, maintaining the mapping relationship with the original object for expansion and collapse during the visualization stage.

[0077] Dependency analysis is performed on the parsed dependency graph object, generating two types of analysis results. Dependency path analysis results are applied to any two sets of component identifiers, generating a set of directed paths based on the adjacency list and access pruning strategy, while recording the path length, the number of transitive edges, and the number of included cycle groups. Isolated component node analysis results are applied to all nodes, filtering out nodes with neither upstream nor downstream connections by counting incoming and outgoing edges. Both types of results maintain bidirectional references to nodes, edges, and cycle groups, facilitating interface interaction and subsequent governance action location. To reduce memory consumption and latency, the path set employs incremental caching and expiration strategies, reusing existing results for repeated queries, and truncating long paths exceeding a threshold while retaining the first and last anchor points and key intermediate nodes.

[0078] Dependency path analysis results and isolated component node analysis results need to be written back to the parsed dependency graph object, which is accomplished using an injection-based association method. For nodes and edges that need to be highlighted, visual labels and weight labels are written; expansion instructions are written for nodes in loop groups; path numbers and sequence numbers are written for path sets to ensure stable positioning of the same path on the interface. Subsequently, a panoramic dependency graph oriented towards interactive presentation is generated, supplementing visual layout information without changing the semantic structure. Layout generation assigns coordinates and hierarchical numbers based on metrics and hierarchical relationships, setting language partition boundaries and cross-partition connection channels for cross-language scenarios; for large-scale graphs, a pagination and tile-based deferred rendering strategy is adopted, loading only the corresponding subgraphs within the viewport and expanding them as needed when triggered by interaction.

[0079] The visual interactive interface is directly bound to the panoramic dependency graph, providing capabilities such as component type attribute filtering, language partition switching, loop group collapsing and expanding, path highlighting and segment-by-segment tracking, one-click location of isolated component nodes, and quick retrieval in the attribute panel. Filtering actions only affect the rendering layer and do not modify the underlying data; path highlighting is driven by path numbers, increasing the drawing priority of corresponding nodes and edges and reducing the opacity of irrelevant elements; isolated component node location focuses on the viewport and displays a list of nodes with zero inbound and outbound edge counts. Interface events are uniformly entered into the event bus, achieving bidirectional synchronization with the memory dependency graph object to ensure consistency between interactive operations and data state. To support long-term operation and multi-user collaboration, the interface layer records view snapshots and filtering conditions, allowing restoration to any analysis point in time.

[0080] This embodiment transforms component objects and dependency relationship objects in the unified dependency description into an operable graph structure through a memory dependency graph object. Cyclic dependency detection and parsing outputs an acyclic or labeled perspective, providing a stable foundation for subsequent path exploration and risk localization. Dependency path analysis results and isolated component node analysis results are written back into the graph structure, forming a carrier integrating data and analysis. The panoramic dependency graph is supplemented with layout and labels, realizing a continuous link from structure generation and semantic annotation to interactive presentation. Through mechanisms such as layered containers, placeholder nodes, deduplication and merging, cyclic group agglomeration, incremental caching, and paginated rendering, the cross-language dependency network can be presented with a unified view and support real-time filtering and localization, reducing the cognitive and investigation costs caused by cross-ecosystem fragmentation. This provides highly consistent input and low-latency entry points for subsequent version constraint solving, environment construction, and vulnerability propagation assessment.

[0081] In one embodiment, step S30 above includes: S301 defines the metadata structure of the unified constraint model, including component identifier objects, version constraint objects, and constraint relationship objects. S302, configure a constraint translation mechanism for each component type that can convert the native version of the constraint syntax of the corresponding component type into the standard format of the unified constraint model; S303, Traverse the component nodes in the panoramic dependency graph and collect the version constraints of all component nodes; S304, The version constraints are converted according to the constraint translation mechanism of the corresponding component type to generate the constraint conditions in the unified constraint model; S305, mark the set of constraints with version conflicts in the unified constraint model, and generate the unified constraint model after conflict marking.

[0082] In this embodiment, the metadata structure of the unified constraint model consists of component identifier objects, version constraint objects, and constraint relationship objects, which together cover the constraint expression space across language ecosystems. The component identifier object is used to uniquely locate dependent entities. Its fields include namespace, name, source domain, language type, and optional content fingerprint. The namespace and name are concatenated to form a global key, and the content fingerprint originates from a stable summary of the original description file entry. The version constraint object is used to represent the set of allowed versions, employing a hybrid structure that combines intervals and sets. Intervals are represented by upper and lower bounds and open / closed attributes, while sets record discrete allowed and excluded versions, additionally recording pre-release bits, build bits, and compatibility semantic tags. The constraint relationship object carries the carrier and propagation relationship of constraint application. Its fields include starting component identifier, ending component identifier, constraint source, transitivity tag, and exclusion list. The source field links to the location path in the original description file for easy traceability.

[0083] The constraint translation mechanism caters to multiple language ecosystems, converting native expressions into a standard format with a unified constraint model. The mechanism is assembled in a plug-in manner, with each component type bound to a translation unit. Each translation unit incorporates a semantic mapping table and a fault-tolerant resolution process. The semantic mapping table maps common expressions to combinations of intervals and sets; for example, square brackets and parentheses in the Java ecosystem map to closed and open intervals, compatible prefixes in the semantic version map to intervals unchanged in the primary version, and multiple clause combinations in Python are mapped to the intersection and union of multiple intervals. The fault-tolerant resolution process handles null values, missing boundaries, and expression ambiguity. When an upper bound is missing, an infinite upper bound marker is recorded; when a lower bound is missing, an infinite lower bound marker is recorded; and when there is expression ambiguity, the original text is backfilled and a manual review marker is added. The translation output is uniformly assigned to a version constraint object and a one-to-many association is established with the component identifier object.

[0084] When traversing component nodes in the comprehensive dependency graph to collect version constraints, a two-level index is first established for the component node set: language partition and source partition. The language partition is divided according to the ecosystem, and the source partition is divided according to the manifest file or lock file. The traversal order follows a combination of in-degree priority and time priority. In-degree priority is used to collect the central component constraints that are referenced by multiple parties as quickly as possible, while time priority is used to prioritize processing the most recently committed source partition. Each time a component node is visited, the native constraint expression, lock version, and derived constraints are read, and constraint entries are generated. Constraint entries contain the original text, source path, ecosystem identifier, and translation unit identifier. After the entry enters the constraint translation mechanism, a version constraint condition object is output; if multiple entries with inconsistent sources appear for the same component, a merging process is initiated.

[0085] The merging process combines version constraint objects at the component identifier object level. It first calculates the interval intersection and merge, then merges the discrete sets, maintaining priority coverage of the excluded sets. When calculating the intersection and merge, multiple intervals are handled using linear scanning and endpoint merging. For open / closed attributes, when endpoints are equal, a half-open / half-closed priority table is used. When discrete sets and intervals overlap, the set priority is given. The merged version constraint objects retain source details and change records, forming traceable composite constraints. If the intersection is empty or the excluded set covers all allowed sets, a conflict entry is generated and the conflict marking process begins.

[0086] The conflict labeling process identifies incompatible sets of constraints within a unified constraint model. The process analyzes the combinations of conflict sources, converging into a minimal conflict set. This minimal conflict set contains only the set of constraint objects that no longer conflict after removing any one element. Each minimal conflict set is assigned a unique identifier, bound to the involved component identifier object and constraint relationship object, and includes a conflict level and diagnostic summary. The conflict level is assessed based on source coverage and propagation range. Source coverage reflects the breadth of cross-regional occurrences, while propagation range reflects the number of downstream objects reachable through constraint relationship objects. The labeled model is defined as the conflict-labeled unified constraint model, and subsequent solutions and adjustments will use this as input.

[0087] To enhance the stability and observability of subsequent processing, the unified constraint model employs a dual-view structure during persistence: a compact view storing merged version constraint objects and the minimum conflict set; and a raw view storing untranslated and unmerged native entries and their source paths. The compact view handles online querying and solving, while the raw view handles auditing and backtracking. A one-to-one correspondence is established between the two views using entry hashes and source paths. The persistence process uses idempotent writes, with the component identifier object serving as the primary key. Version constraint objects and constraint relationship objects are annotated with version vectors to track change paths, ensuring that duplicate imports do not introduce duplicate entities. To facilitate real-time retrieval and analysis in large-scale scenarios, multi-column indexes are created for component identifiers, language types, major versions, and minimum conflict set identifiers, and range indexes are created for interval endpoints.

[0088] To address the special cases introduced by cross-language differences, the constraint translation mechanism and merging process provide extended bits. Pre-release and build bits are included in the comparison sequence via priority bit markers, with the inclusion and exclusion comparison order recorded in the constraint object. Aliases and renaming are aligned to the unified component identifier object through an equivalence mapping table derived from equivalence relation inference and manual registration during the parsing phase. Platform and architecture constraints are attached to the version constraint object via environment dimension tags; during merging, different environment dimensions are calculated separately and the results are retained. In this way, the unified constraint model neither loses ecological details nor compromises cross-ecological alignment capabilities.

[0089] This embodiment transforms the scattered version representations across multiple ecosystems into a comparable, mergeable, and traceable standard structure through a unified constraint model. The constraint translation mechanism and merging process converge semantic differences and source discrepancies into a unified representation of intervals and sets. The minimum conflict set ensures that the conflict location and cause exist as explicit entities. By coexisting with compact views and original text views, online processing achieves efficient retrieval and stable input, while auditing and backtracking provide a complete chain of evidence.

[0090] In one embodiment, step S40 above includes: S401 uses constraint solving methods to process the unified constraint model after conflict marking in order to find version combinations that satisfy all constraints. S402, when the constraint solving method successfully finds a version combination that satisfies all constraints, the found version combination is determined as a compatible version combination; S403, when the constraint solving method fails to find a version combination that satisfies all constraints, extract the set of key constraints that cause the conflict from the unified constraint model after the conflict marker; S404, Based on the preset solution mechanism library, generate multiple version adjustment schemes for the set of key constraints; S405, Analyze the priority of the multiple version adjustment schemes, select the version adjustment scheme with the highest priority and apply it to the unified constraint model after the conflict mark to generate the adjusted unified constraint model; S406, The adjusted unified constraint model is processed using the constraint solving method to determine a compatible combination of versions.

[0091] In this embodiment, when processing the unified constraint model to determine compatible version combinations, the input is the unified constraint model after conflict marking and the set of component nodes covered by dependency edges. The output is a set of version assignments that simultaneously satisfy version constraints, propagation relationships, and exclusion conditions globally. First, the domain space and constraint relationships are organized. The domain space originates from the version constraint object in the unified constraint model. A candidate version set and interval representation are generated for each component node, preserving open / closed attributes, discrete allowed sets, and excluded sets, and recording the source path and priority label. The transitivity markers and exclusion lists in the constraint relationship object are mapped to cross-component linkage constraints, and dependency edges are used to limit the version compatibility relationship and path reachability requirements between upstream and downstream components. To ensure process reproducibility, all component nodes and candidate versions are arranged in a stable order; source labels and time labels are only used for tracing and do not change the solution order.

[0092] The constraint solving method uses the unified constraint model after conflict marking as the sole basis. It first performs a satisfiability determination, then derives a set of version assignments that satisfy the constraints. The satisfiability determination matches the candidate versions of each component node with its associated interval constraints and exclusion sets, eliminating candidates that do not fall within the valid domain. For component nodes with upstream dependencies, candidates incompatible with the upstream are filtered out based on the propagation requirements and transitivity markers in the dependency edges. For constraints with environment dimension labels, candidate views are built separately for each environment dimension to avoid erroneous merging across environments. If all component nodes still retain at least one candidate, the assignment derivation phase begins. The assignment derivation phase selects candidate options for component nodes in a stable order. Each selection simultaneously checks the cross-constraints and dependency propagation constraints with the already selected option. If a selection causes subsequent candidate options to be completely eliminated, the process backtracks and tries the next candidate option on the same node until a complete assignment is derived or the constraint is determined to be unsatisfiable.

[0093] When satisfiability determination fails or the assignment derivation process cannot be completed, it is necessary to extract the set of key constraints leading to unsatisfiability from the unified constraint model after conflict marking. The key set extraction aims to minimize this set, progressively removing constraint entries that have no direct causal relationship with the current conflict, retaining the minimum set from which removing any one entry can resolve the conflict. This set is bound to the involved component identifier object and constraint relationship object, recording the source partition, propagation scope, and affected paths. This guides subsequent adjustment phases to only apply to the necessary minimum scope, avoiding collateral changes to unrelated components.

[0094] The solution library provides multiple version adjustment schemes for sets of key constraints, each corresponding to an executable combination of changes. These schemes can slightly relax upper or lower bounds while maintaining compatible semantics, introduce adjacent stable versions into the discrete allowable set, enable equivalent component mapping to replace renamed dependencies, apply exclusion lists to block unnecessary transitive dependency chains, and employ source switching to unify version sources. Each version adjustment scheme is evaluated during generation for consistency with the source, synergy with the propagation path, and consistency with historical locking records, generating a change impact overview, including the number of affected dependency edges, the number of potential cascading adjustments, and the magnitude of the safety baseline shift. Version adjustment schemes do not directly rewrite the unified constraint model; instead, they form candidate change sets and verification plans for subsequent priority analysis and replay verification.

[0095] The priority analysis of multiple version adjustment schemes constructs a scoring vector based on feasibility, impact, stability, and security as the main dimensions. The feasibility dimension focuses on whether the changes immediately resolve contradictions in the critical set; the impact dimension focuses on the number of component nodes and dependency edges requiring synchronous changes; the stability dimension focuses on the frequency of candidate versions appearing in the unified dependency description and historical locking records; and the security dimension focuses on the status of the target version in the vulnerability information source and whether it triggers additional vulnerability fixes. The version adjustment scheme with the highest priority is selected and applied to the unified constraint model after conflict marking, forming the adjusted unified constraint model. The application process follows the principles of idempotency and replayability, tagging the adjusted constraint items with version vector labels, pre-change and post-change images are preserved, and the source path and operation time are recorded for subsequent rollback and auditing.

[0096] The adjusted unified constraint model is then processed again using the constraint solving method. Since the critical set has been specifically resolved, the satisfiability determination usually passes, leading to a complete assignment. The resulting output is solidified into a compatible version combination, accompanied by three types of information. The first is source proof, recording the source entries for each assignment and the adopted version constraint objects. The second is a dependency path summary, recording the critical path, transit edge count, and loop group expansion information to ensure that subsequent environment configuration and dependency installation can be replayed from the same perspective. The third is a conflict resolution description, recording the adopted version adjustment schemes and abandoned schemes, providing specific entries for critical set resolution, forming an end-to-end interpretable link. If it is still unsatisfiable, the critical set extraction, scheme generation, priority analysis, and model adjustment are repeated until a compatible version combination is derived or the determination fails to provide a solution under the current source and environment dimensions.

[0097] To improve processing efficiency and stability, incremental solving and caching mechanisms are introduced. When the unified constraint model changes only on a small number of component nodes, satisfiability determination and assignment derivation are performed only on the affected subgraphs, reusing existing assignments and associated information from the unaffected parts. To avoid inconsistent results in different operating environments, stable ordering and deterministic selection rules are introduced. Candidates with the same score are selected according to component identifier and version lexicographical order, and content summaries and location information are recorded on all intermediate results to ensure that the same input always yields the same output.

[0098] This embodiment processes a unified constraint model and determines compatible version combinations, enabling consistent determination and global assignment of cross-language and cross-origin version restrictions within a single semantic space. The set of key constraints compresses the reasons for unmet constraints into a minimal set, and the resolution mechanism library covers common conflict scenarios with multiple version adjustment schemes. Priority analysis ensures a balance between feasibility and impact, and the adjusted unified constraint model provides focused input for subsequent solutions. This forms a self-consistent closed loop, with traceability and replayability from conflict marking to solution generation and compatible assignment. This significantly reduces the cost of manual investigation and repeated trial and error, improves the consistency and stability of version selection, and provides a definite and reusable version baseline for subsequent environment configuration, dependency installation, and security governance.

[0099] In one embodiment, step S50 above includes: S501, parse the environment configuration part in the unified dependency description to obtain the runtime version information of the required components and the toolchain version information; S502, Based on the component runtime version information, obtain and install the specified version of the component runtime; S503, Based on the toolchain version information, obtain and install the specified version of the development toolchain; S504 creates a separate virtual environment for each component type and deploys the installed component runtime and development toolchain to the corresponding virtual environment; S505 configures the system paths and environment variables between virtual environments to ensure isolation and conflict-free environments. S506 generates an environment lock file that records the runtime versions of all installed components and the versions of the development toolchain.

[0100] In this embodiment, the environment configuration section of the unified dependency description carries the basic conditions required for the execution and build phases of multi-language engineering. The parsing process loads structured nodes from the unified dependency description, extracts the environment configuration section, and generates a mapping with component type as the key. Each mapping item contains component runtime version information, toolchain version information, platform and architecture constraints, image and artifact source, verification summary, and source path. The parser performs pattern verification and value range verification on the fields. Missing fields trigger a backfilling strategy: extracting the most recently verified record from the locked list or historical snapshot, while retaining the source mark to ensure a clear link for subsequent auditing and backtracking. The cleaned environment configuration data is written to the memory cache and event bus, and environment configuration data in a unified format is published to the downstream installation process.

[0101] Component runtime version information is used to indicate the version baseline of the language layer and execution layer. During the acquisition and installation phases, artifacts are pulled according to the source path and version indication in the environment configuration data. Dual-channel verification (content digest and supply chain provenance) is enabled during the download phase. During the unpacking phase, the corresponding binary or bytecode distribution package is mapped based on the platform and architecture. The installation location follows a reproducible directory layout, employing a strategy of separating the read-only base layer from the writable patch layer to prevent subsequent toolchain writes from polluting the runtime. After installation, version probe commands and dynamic link probes are executed to record the actual version, dependency chain, and system library bindings. If these are inconsistent with the component runtime version information, the deviation is immediately marked, and the deployment phase is blocked.

[0102] The toolchain version information covers the compiler, builder, packager, debugger, and dependency manager. The installation process generates command sequences based on the toolchain version information, prioritizing local caches and private images to reduce the impact of network jitter. For tools containing native primitives or kernel interfaces, kernel capability detection and minimum kernel version verification are introduced, selecting compatible builds when necessary. Toolchain installation also employs a dual-track recording system of verification and proof of origin, with tool binaries and their plugins stored separately on disk for fine-grained upgrades and rollbacks. The toolchain is registered in the environment index, including its name, version, executable path, patch layer number, and signature status.

[0103] Virtual environments are used to achieve runtime and tool isolation across component types. An independent space is created for each component type, containing a runtime directory, toolchain directory, dependency cache, and temporary build area. During space initialization, an activation script and environment snapshot are generated. The activation script sets PATH, LD_LIBRARY_PATH (or an equivalent mechanism), language-specific module paths, certificate storage locations, and private repository credential mount points. During deployment, component runtimes and development toolchains are aligned to their respective virtual environments according to a mapping table. Symbolic links are only established within the same component type; cross-component type calls are always made through explicit entry points or wrappers, eliminating implicit crosstalk.

[0104] System paths and environment variables are configured following the principle of "isolation first, explicit exposure." Isolation is achieved through namespaced directories and prefixed environment variable names; explicit exposure is achieved by exporting a small number of cross-environment shared paths through a controlled manifest, such as a general certificate directory and a cross-language build cache. The conflict detection engine performs three types of checks before writing to the path: executable name conflicts, dynamic library symbol conflicts, and out-of-bounds changes. When a conflict is found, a rewrite strategy is selected according to a priority table (name wrapper, namespace prefix, path reordering), and the final decision is written to the change log. To reduce lookup jitter caused by long PATH chains, a path index file is generated and loaded all at once by the activation script, ensuring a deterministic lookup order for processes within the session.

[0105] The environment lock file records all the details and dependencies required for environment reconstruction. The generation process retrieves the current state from the environment index and virtual environment list, writing component runtime and toolchain versions, download sources, verification summaries, installation paths, activation script summaries, system library bindings, platform and architecture, environment variable whitelists, wrapper mappings, and cache fingerprints. The lock file uses stable sorting and content-addressable storage; any field change will cause a fingerprint change. Two views are generated: a compressed version for quick comparison between builds and deployments, and an audit version to retain source proof and signature for compliance checks. After writing, a rebuildability self-check is performed: the environment build is replayed in an isolated sandbox according to the lock file, comparing the runtime probe and toolchain probe outputs. If differences exist, the process backtracks to the differing fields and fills in the missing metadata in the lock file.

[0106] In cross-platform and distributed scenarios, the environment configuration engine supports matrix-based adaptation. Platform and architecture dimensions are driven by environment configuration data to generate variants. These variants share upper-layer logic while differentiating themselves by binding to underlying artifacts and system libraries. Distributed build nodes receive environment configuration data and lock files via remote execution interfaces, reconstruct locally according to the same process, and report fingerprint and probe results, which the master control unit uses to determine consistency. A three-layer caching strategy is employed: a remote mirror layer, a local mirror layer, and a working area cache layer. Hit order ensures minimal pull latency while maintaining consistency. The entire chain achieves replayability through transactional steps and idempotent commands, allowing recovery from any failure point based on checkpoints in the logs.

[0107] This embodiment accurately extracts environment configuration data from a unified dependency description, and based on this, installs component runtimes and development toolchains, builds independent virtual environments, configures system paths and environment variables, and generates environment lock files. This provides multi-language projects with a reproducible, auditable, and replayable integrated execution foundation. The runtime and toolchain are constrained by verification and proof of origin for consistency; virtual environment isolation eliminates implicit interference across component types; conflict detection and wrapper mechanisms reduce the risk of path and dynamic library conflicts; and lock files and replay self-checks solidify the environment state into a deterministic product. This provides a stable entry point for subsequent dependency installation, version upgrades, and security governance, significantly reducing the costs associated with environment drift and integration failures, and improving the stability and controllability of cross-language collaborative development and continuous delivery.

[0108] In one embodiment, step S70 above includes: S701 integrates application programming interfaces from multiple vulnerability databases and deduplicatizes and normalizes them to form an integrated vulnerability information source. S702, Match the component node versions in the panoramic dependency graph with the integrated vulnerability information source to identify components with vulnerabilities; S703, Analyze all affected paths of the vulnerable component in the panoramic dependency map and generate a vulnerability impact range report; S704. Based on the vulnerability impact report, find an available security version for each vulnerable component, verify the compatibility of the security version with existing dependency constraints, and generate a compatibility verification result. S705, Based on the compatibility verification results, generate modification instructions to synchronously update the unified dependency description and the corresponding component-specific description file.

[0109] In this embodiment, a collector is first established for each external library. The collector pulls incremental notifications within a time window, extracting vulnerability IDs, component namespaces, affected version ranges, remediation suggestions, severity levels, and reference links. These are then mapped to dependent ecosystem names and package coordinates using a unified key space. Differences between names and coordinates are resolved using an equivalence mapping table derived from the alias set of component identifiers, the correspondence between mirror repository coordinates and version control paths. Affected version ranges are standardized as a combination of upper and lower bounds and open / closed attributes, with discrete versions and excluded versions merged into a set representation. After normalization, entries are deduplicated, with the deduplication key consisting of the vulnerability ID and component equivalence class. When differences in the impact range provided by different information sources occur, a merged range is constructed and labeled with source coverage and confidence weights for adjudication during the matching phase.

[0110] Matching the panoramic dependency graph with integrated vulnerability information sources prioritizes version standardization. For each component node, a unique identifier, version number, language ecosystem, and source domain are extracted. The version number is standardized into a comparable three- or four-segment structure, retaining pre-release and build bits. The matching engine selects the corresponding matcher based on the ecosystem dimension. First, it maps the node identifier to the coordinates used by the information source using an equivalence mapping table. Then, it performs interval inclusion and set inclusion checks on the impact interval. If multiple announcements provide overlapping intervals for the same node, the more stringent combination result is selected based on confidence weight and source coverage, and a conflict flag is added. Simultaneously, a bidirectional association index between component nodes and vulnerability entries is generated during the matching phase. This index carries the impact interval, suggested version set, and severity level, serving as direct input for subsequent path analysis and remediation instruction generation.

[0111] Affected path analysis is performed on the parsed dependency graph object for each matched component node. The algorithm starts at that node, traversing upwards along incoming edges until reaching a boundary node with no upstream, while simultaneously traversing downwards along outgoing edges to discover downstream links that propagate the impact. During traversal, linguistic ecology and scope labels are preserved to distinguish between build-time and runtime impacts. To control complexity, path generation employs hierarchical pruning and cycle-removal expansion: when encountering a cycle group, it is represented as a clustered node, and its internal members and the sequence of edges within the cycle are preserved for the report; when encountering duplicate sub-paths, the previously calculated summary results are reused. The final vulnerability impact report includes the set of affected paths, the set of entry components, the distribution of linguistic partitions, cycle group markers, and the distribution of severity levels. A propagation weight (calculated by path length, the number of propagating edges, and entry importance) is calculated for each path for use in deriving subsequent remediation priority sequences.

[0112] Security version lookup and compatibility verification are conducted with the impact scope report as the constraint boundary. For each component with a vulnerability, candidate security versions are compiled from the remediation suggestion set in the vulnerability entry, historical release streams, and trusted mirror index. Versions still within the impact range or marked as insecure by other announcements are removed, resulting in a security candidate set. The security candidate set is cross-validated with a unified constraint model. First, a range compatibility check is performed to ensure that the candidate version falls within the valid domain of the component in the unified constraint model. Then, propagation consistency checks are performed on upstream and downstream based on dependency edges to verify that the candidate version does not violate upstream requirements for interfaces or introduce exclusion conditions downstream. If the system has environment dimension labels, verification is performed on each dimension separately to avoid cross-platform misadaptation. The verification results form the compatibility verification results, recording the replaceable candidate set, the reasons for exclusion, the list of nodes on the affected path that need to be evaluated synchronously, and a propagation consistency summary.

[0113] Modification instructions are generated and output as transactional change sets. For each verified candidate security version, a minimum change unit is generated, including the location path, target version, pre-change summary, and post-change summary from the unified dependency description. If the component has a redundant explicit version in its component-specific description file, a change unit for that file is generated synchronously to ensure semantic consistency. The same component and its necessary synchronization items are grouped into atomic groups, with each group appended a replay sequence number and dependency order constraints to ensure consistency across file updates. A dry run verification is performed before applying the changes: a subset of the candidate comprehensive dependency graph is reconstructed based on the changed unified dependency description, checking for new version conflicts or disruption of established compatible version combinations. After successful dry run, an executable modification instruction list is output, along with a check-in of the change source, vulnerability number, affected path summary, and compatibility verification result summary for subsequent executor execution and system archiving.

[0114] This embodiment provides a consistent data entry point through vulnerability information source deduplication and semantic normalization. The matching process establishes a precise correspondence between component nodes and affected areas. Affected path analysis transforms isolated vulnerabilities into traceable propagation chains. Security version lookup and compatibility verification align remediation recommendations with a unified constraint model. Transactional modification instructions ensure that unified dependency descriptions and component-specific description files are updated synchronously and have replayability. This forms a closed loop from identification to remediation, reducing security governance costs in a multi-language, multi-ecosystem dependency network with low-ambiguity data, auditable processes, and atomic changes. It also reduces the risk of remediation oversights and version rollbacks, providing a definite and consistent security baseline for subsequent building, deployment, and compliance auditing.

[0115] In one embodiment, a dependency processing apparatus for multi-component projects is provided, which corresponds one-to-one with the dependency processing methods for multi-component projects described in the above embodiments. (Refer to...) Figure 3 , Figure 3 This is a schematic diagram of the functional modules of a preferred embodiment of the dependency processing device for multi-component projects of the present invention. The modules include a dependency modeling module 10, a graph construction module 20, a constraint modeling module 30, a compatibility solving module 40, an environment configuration module 50, a dependency deployment module 60, and a vulnerability repair module 70. Detailed descriptions of each functional module are as follows: The dependency modeling module 10 is used to parse multiple component-specific description files in the project that correspond to different component types, extract dependency data from the multiple component-specific description files, and generate a unified dependency description based on the dependency data; Graph construction module 20 is used to construct a panoramic dependency graph containing component nodes and dependency edges connecting the component nodes based on the unified dependency description. The constraint modeling module 30 is used to identify the version constraints of at least one component node in the panoramic dependency graph and generate a unified constraint model based on the version constraints. The compatibility solver module 40 is used to determine compatible version combinations for component nodes connected by dependency edges by processing the unified constraint model; The environment configuration module 50 is used to extract environment configuration data from the unified dependency description and install the corresponding runtime and tools according to the environment configuration data to configure the multi-component operating environment. Dependency deployment module 60 is used to install project dependencies in the multi-component operating environment according to the compatible version combination; The vulnerability remediation module 70 is used to scan the component nodes in the panoramic dependency graph based on the vulnerability information source to identify the components with vulnerabilities, and generate remediation instructions for modifying the unified dependency description to update the version of the components with vulnerabilities.

[0116] In one embodiment, the dependency modeling module 10 is specifically used for: Define a metadata model for a unified dependency description language, wherein the metadata model includes project objects, component objects, and dependency objects; Configure a corresponding parser adapter for each component type that can understand the syntax structure of the native description file of the corresponding component type; Using the resolver adapter configured for each component type, read and parse multiple component-specific description files in the project corresponding to different component types, and extract dependency data containing component identifiers and version constraints from the multiple component-specific description files; The dependency data is mapped according to the metadata model and converted into a unified dependency description language format to generate a unified dependency description. The unified dependency description is stored in a graph database to convert the component object into a graph node in the graph database and the dependency object into a graph edge in the graph database.

[0117] In one embodiment, the map construction module 20 is specifically used for: Based on the component objects and dependency relationship objects in the unified dependency description, an in-memory dependency graph object is constructed. The dependency graph object consists of component nodes representing components and dependency edges representing dependencies. Circular dependencies in the dependency graph object are detected, and the detected circular dependencies are parsed to generate a parsed dependency graph object. Dependency analysis is performed on the parsed dependency graph object to obtain dependency path analysis results and isolated component node analysis results. The dependency path analysis results and the isolated component node analysis results are associated with the parsed dependency graph object to generate a panoramic dependency graph for visualization analysis. Provides a visual interactive interface for the panoramic dependency map.

[0118] In one embodiment, the constraint modeling module 30 is specifically used for: The metadata structure defining the unified constraint model includes component identifier objects, version constraint objects, and constraint relationship objects; Configure a constraint translation mechanism for each component type that can convert the native version of the constraint syntax of the corresponding component type into a standard format of the unified constraint model; Traverse the component nodes in the panoramic dependency graph and collect the version constraints of all component nodes; The version constraints are converted according to the constraint translation mechanism of the corresponding component type to generate the constraint conditions in the unified constraint model; In the unified constraint model, mark the set of constraints with version conflicts to generate the unified constraint model after conflict marking.

[0119] In one embodiment, the compatible solver module 40 is specifically used for: Constraint solving methods are used to process the unified constraint model after conflict marking in order to find version combinations that satisfy all constraints. When the constraint solving method successfully finds a version combination that satisfies all constraints, the found version combination is determined as a compatible version combination. When the constraint solving method fails to find a version combination that satisfies all constraints, the set of key constraints that cause the conflict is extracted from the unified constraint model after the conflict marker. Based on a pre-defined solution mechanism library, multiple version adjustment schemes are generated for the set of key constraints. Analyze the priorities of the various version adjustment schemes, select the version adjustment scheme with the highest priority and apply it to the unified constraint model after the conflict mark to generate the adjusted unified constraint model; The adjusted unified constraint model is processed using the constraint solving method described above to determine compatible version combinations.

[0120] In one embodiment, the environment configuration module 50 is specifically used for: Parse the environment configuration section in the unified dependency description to obtain the runtime version information of the required components and the toolchain version information; Based on the component runtime version information, obtain and install the specified version of the component runtime; Based on the toolchain version information, obtain and install the specified version of the development toolchain; Create a separate virtual environment for each component type, and deploy the installed component runtime and development toolchain to the corresponding virtual environment; Configure system paths and environment variables between virtual environments to ensure isolation and conflict-free operation between them; Generates an environment lock file that records the runtime versions of all installed components and the versions of the development toolchain.

[0121] In one embodiment, the vulnerability repair module 70 is specifically used for: The application programming interfaces of multiple vulnerability databases are integrated and deduplicated to form an integrated vulnerability information source. The component node versions in the panoramic dependency graph are matched with the integrated vulnerability information source to identify components with vulnerabilities. Analyze all affected paths of the vulnerable components in the panoramic dependency graph and generate a vulnerability impact scope report; Based on the vulnerability impact report, find available security versions for each vulnerable component, verify the compatibility of the security versions with existing dependency constraints, and generate compatibility verification results. Based on the compatibility verification results, modification instructions are generated to synchronously update the unified dependency description and the corresponding component-specific description files.

[0122] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides determination and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it implements server-side functions or steps of a dependency processing method for a multi-component project.

[0123] In one embodiment, a computer device is provided, which may be a client, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides determination and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with an external server via a network connection. When executed by the processor, the computer program implements client-side functions or steps of a dependency processing method for a multi-component project.

[0124] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: The project parses multiple component-specific description files corresponding to different component types, extracts dependency data from these multiple component-specific description files, and generates a unified dependency description based on the dependency data. Based on the unified dependency description, a panoramic dependency graph containing component nodes and dependency edges connecting the component nodes is constructed. Identify the version constraints of at least one component node in the panoramic dependency graph, and generate a unified constraint model based on the version constraints; By processing the unified constraint model, compatible version combinations are determined for component nodes connected by dependency edges; Environment configuration data is extracted from the unified dependency description, and the corresponding runtime and tools are installed according to the environment configuration data to configure the multi-component operating environment; Install project dependencies in the multi-component operating environment according to the compatible version combination; Based on the vulnerability information source, the component nodes in the panoramic dependency graph are scanned to identify vulnerable components, and a repair instruction is generated to modify the unified dependency description to update the version of the vulnerable component.

[0125] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: The project parses multiple component-specific description files corresponding to different component types, extracts dependency data from these multiple component-specific description files, and generates a unified dependency description based on the dependency data. Based on the unified dependency description, a panoramic dependency graph containing component nodes and dependency edges connecting the component nodes is constructed. Identify the version constraints of at least one component node in the panoramic dependency graph, and generate a unified constraint model based on the version constraints; By processing the unified constraint model, compatible version combinations are determined for component nodes connected by dependency edges; Environment configuration data is extracted from the unified dependency description, and the corresponding runtime and tools are installed according to the environment configuration data to configure the multi-component operating environment; Install project dependencies in the multi-component operating environment according to the compatible version combination; Based on the vulnerability information source, the component nodes in the panoramic dependency graph are scanned to identify vulnerable components, and a repair instruction is generated to modify the unified dependency description to update the version of the vulnerable component.

[0126] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0127] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0128] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0129] It should be noted that if any software tools or components not belonging to this company appear in the embodiments of this application, they are merely illustrative examples and do not represent actual use. The embodiments described above are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A dependency handling method for multi-component projects, characterized in that, Includes the following steps: The project parses multiple component-specific description files corresponding to different component types, extracts dependency data from these multiple component-specific description files, and generates a unified dependency description based on the dependency data. Based on the unified dependency description, a panoramic dependency graph containing component nodes and dependency edges connecting the component nodes is constructed. Identify the version constraints of at least one component node in the panoramic dependency graph, and generate a unified constraint model based on the version constraints; By processing the unified constraint model, compatible version combinations are determined for component nodes connected by dependency edges; Environment configuration data is extracted from the unified dependency description, and the corresponding runtime and tools are installed according to the environment configuration data to configure the multi-component operating environment; Install project dependencies in the multi-component operating environment according to the compatible version combination; Based on the vulnerability information source, the component nodes in the panoramic dependency graph are scanned to identify vulnerable components, and a repair instruction is generated to modify the unified dependency description to update the version of the vulnerable component.

2. The dependency handling method for multi-component projects as described in claim 1, characterized in that, The project parses multiple component-specific description files corresponding to different component types, extracts dependency data from these files, and generates a unified dependency description based on this data, including: Define a metadata model for a unified dependency description language, wherein the metadata model includes project objects, component objects, and dependency objects; Configure a corresponding parser adapter for each component type that can understand the syntax structure of the native description file of the corresponding component type; Using the resolver adapter configured for each component type, read and parse multiple component-specific description files in the project corresponding to different component types, and extract dependency data containing component identifiers and version constraints from the multiple component-specific description files; The dependency data is mapped according to the metadata model and converted into a unified dependency description language format to generate a unified dependency description. The unified dependency description is stored in a graph database to convert the component object into a graph node in the graph database and the dependency object into a graph edge in the graph database.

3. The dependency handling method for multi-component projects as described in claim 1, characterized in that, Based on the unified dependency description, a panoramic dependency graph is constructed, including component nodes and dependency edges connecting the component nodes, comprising: Based on the component objects and dependency relationship objects in the unified dependency description, an in-memory dependency graph object is constructed. The dependency graph object consists of component nodes representing components and dependency edges representing dependencies. Circular dependencies in the dependency graph object are detected, and the detected circular dependencies are parsed to generate a parsed dependency graph object. Dependency analysis is performed on the parsed dependency graph object to obtain dependency path analysis results and isolated component node analysis results. The dependency path analysis results and the isolated component node analysis results are associated with the parsed dependency graph object to generate a panoramic dependency graph for visualization analysis. Provides a visual interactive interface for the panoramic dependency map.

4. The dependency handling method for multi-component projects as described in claim 1, characterized in that, Identify version constraints of at least one component node in the panoramic dependency graph, and generate a unified constraint model based on the version constraints, including: The metadata structure defining the unified constraint model includes component identifier objects, version constraint objects, and constraint relationship objects; Configure a constraint translation mechanism for each component type that can convert the native version of the constraint syntax of the corresponding component type into a standard format of the unified constraint model; Traverse the component nodes in the panoramic dependency graph and collect the version constraints of all component nodes; The version constraints are converted according to the constraint translation mechanism of the corresponding component type to generate the constraint conditions in the unified constraint model; In the unified constraint model, mark the set of constraints with version conflicts to generate the unified constraint model after conflict marking.

5. The dependency handling method for multi-component projects as described in claim 1, characterized in that, By processing the unified constraint model, a compatible combination of versions is determined for component nodes connected by dependency edges, including: Constraint solving methods are used to process the unified constraint model after conflict marking in order to find version combinations that satisfy all constraints. When the constraint solving method successfully finds a version combination that satisfies all constraints, the found version combination is determined as a compatible version combination. When the constraint solving method fails to find a version combination that satisfies all constraints, the set of key constraints that cause the conflict is extracted from the unified constraint model after the conflict marker. Based on a pre-defined solution mechanism library, multiple version adjustment schemes are generated for the set of key constraints. Analyze the priorities of the various version adjustment schemes, select the version adjustment scheme with the highest priority and apply it to the unified constraint model after the conflict mark to generate the adjusted unified constraint model; The adjusted unified constraint model is processed using the constraint solving method described above to determine compatible version combinations.

6. The dependency handling method for multi-component projects as described in claim 1, characterized in that, Extracting environment configuration data from the unified dependency description, and installing the corresponding runtime and tools based on the environment configuration data to configure a multi-component operating environment, including: Parse the environment configuration section in the unified dependency description to obtain the runtime version information of the required components and the toolchain version information; Based on the component runtime version information, obtain and install the specified version of the component runtime; Based on the toolchain version information, obtain and install the specified version of the development toolchain; Create a separate virtual environment for each component type, and deploy the installed component runtime and development toolchain to the corresponding virtual environment; Configure system paths and environment variables between virtual environments to ensure isolation and conflict-free operation between them; Generates an environment lock file that records the runtime versions of all installed components and the versions of the development toolchain.

7. The dependency handling method for multi-component projects as described in claim 1, characterized in that, Based on vulnerability information sources, the component nodes in the panoramic dependency graph are scanned to identify vulnerable components, and remediation instructions are generated to modify the unified dependency description to update the version of the vulnerable components, including: The application programming interfaces of multiple vulnerability databases are integrated and deduplicated to form an integrated vulnerability information source. The component node versions in the panoramic dependency graph are matched with the integrated vulnerability information source to identify components with vulnerabilities. Analyze all affected paths of the vulnerable components in the panoramic dependency graph and generate a vulnerability impact scope report; Based on the vulnerability impact report, find available security versions for each vulnerable component, verify the compatibility of the security versions with existing dependency constraints, and generate compatibility verification results. Based on the compatibility verification results, modification instructions are generated to synchronously update the unified dependency description and the corresponding component-specific description files.

8. A dependency handling device for multi-component projects, characterized in that, The dependency handling device for the multi-component project includes: The dependency modeling module is used to parse multiple component-specific description files in the project that correspond to different component types, extract dependency data from the multiple component-specific description files, and generate a unified dependency description based on the dependency data; The graph construction module is used to construct a panoramic dependency graph containing component nodes and dependency edges connecting the component nodes based on the unified dependency description. The constraint modeling module is used to identify the version constraints of at least one component node in the panoramic dependency graph and generate a unified constraint model based on the version constraints. A compatibility solving module is used to determine compatible version combinations for component nodes connected by dependency edges by processing the unified constraint model; The environment configuration module is used to extract environment configuration data from the unified dependency description and install the corresponding runtime and tools according to the environment configuration data to configure the multi-component operating environment. A dependency deployment module is used to install project dependencies in the multi-component operating environment according to the compatible version combination; The vulnerability remediation module is used to scan the component nodes in the panoramic dependency graph based on the vulnerability information source to identify components with vulnerabilities, and generate remediation instructions for modifying the unified dependency description to update the version of the component with vulnerabilities.

9. A computer device, characterized in that, The computer device includes a memory, a processor, and a dependency handler for a multi-component project stored in the memory and executable on the processor. When executed by the processor, the dependency handler for the multi-component project implements the steps of the dependency handling method for a multi-component project as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a dependency handler for a multi-component project, which, when executed by a processor, implements the steps of the dependency handling method for a multi-component project as described in any one of claims 1-7.

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