32 results about "Component (UML)" patented technology

A software package is received and unpacked into multiple components comprising plural functions. Each function is lifted from machine code into static single-assignment intermediate representation and tokenized to produce semantics-preserving embeddings. Intermediate-representation data-flow features are extracted, including detection of constant static variables on a stack, stack reaching definitions, uninitialized variables, and intra-procedural aliases. For each component, the embeddings and features are input to a machine-learning model trained on semantic properties derived from a corpus of software packages to generate a software supply chain risk level. Data characterizing the risk level is provided to a consuming application. When the risk level satisfies a remediation criterion, a remediation action is initiated, including generation of a source-code patch recommendation for an identified root-cause function, insertion of a runtime guard into the component, or issuance of a security advisory for distribution to a security operations dashboard.

The invention discloses a multi-language PLC configuration software component library expansion method and system based on LLVM, and relates to the technical field of configuration software, the method comprises the following steps: obtaining language source codes of various types of programming languages supporting the LLVM front end; inputting the language source code of each type of programming language into a corresponding LLVM front-end compiler, and converting the language source code into a standard intermediate representation; establishing a general language characteristic analysis framework; establishing a general abstract metadata injection framework; building a mapping rule framework; integrating the general language framework, the general abstract metadata injection framework, the mapping rule framework and the output result, and generating a unified extended intermediate representation; and generating an interface component library conforming to the IEC standard. According to the method, any programming language with an LLVM front end is supported, a developer can directly utilize a mature algorithm library in each language ecosystem to select the programming language most suitable for a specific application scene, and the development period is remarkably shortened.

The invention provides a CAE modeling and grid dividing method and system based on natural language driving, and the method comprises the steps: constructing a triple language model, defining an action-object-adversity triple structure, receiving a natural language instruction, carrying out the standardization processing of the instruction, recognizing and extracting the action, object and adversity components in the instruction, and carrying out the recognition and extraction of the action, object and adversity components in the instruction. The missing necessary parameters are prompted and complemented; based on a predefined analysis rule, extracting a triple conforming to the triple structure from the processed instruction; mapping the triad passing the verification into a corresponding CAE operation instruction through a mapping rule base, and generating an instruction sequence according to a logic sequence of a CAE modeling process; and automatically executing the instruction sequence, completing CAE modeling and grid division operations, and finally outputting a CAE model file. According to the method, the user operation complexity and the professional threshold are remarkably reduced, the modeling efficiency and the model quality are improved, an efficient and intelligent auxiliary tool is provided for engineering design, and the wide application value is achieved.

The invention discloses an interactive front-end generation method and system based on API specifications and multiple intelligent experience certificates, and belongs to the field of front-end software development automation. A double-stage intelligent generation framework is adopted, natural language query and back-end API specifications of a user are received, an optimal retrieval stage and an iteration generation stage are executed in sequence, and a code version with the highest comprehensive score is selected from iteration history to serve as a generated interactive front-end prototype code. Wherein in the retrieval stage, related UI components, icons and general layout structures are accurately retrieved to provide a high-quality context; a closed-loop optimization process dominated by an encoder and coordinated by multiple agents is started in iteration generation, the code quality is verified in a multi-dimensional mode, and the encoder agents are driven to conduct multi-round iteration correction on the code according to the verification result. And finally, the prototype code preferentially output can perform real data interaction with a back-end API, and can be used as a Demo or a starting point for rapid development, so that the front-end development efficiency is remarkably improved.

The invention relates to the technical field of data enhancement and system engineering, in particular to a user behavior data enhancement method of a large language model based on RFLP driving. Comprising the steps of determining a core driving problem and an expected application scene of to-be-generated user behavior data, determining a task target, a data structure requirement, a data characteristic requirement, a constraint condition and a non-functional requirement of a large language model data generation system based on RFLP driving according to the core driving problem and the expected application scene, and encoding the requirement specifications into a plurality of functional modules; and forming a data generation function set according to the modules, constructing a logic scheme based on'strategy-component-combination 'for the system based on the function set, converting the logic scheme into an executable scheme, finally controlling the large language model to execute the executable scheme, and generating to-be-generated user behavior data. Therefore, the problem that the cue word is difficult to ensure the quality and consistency of the generated data is solved, and a scientific methodological support is provided for constructing a high-quality, controllable and extensible synthetic user data generation system.

Described herein are systems utilizing a DevSecOps model comprising a CI / CD template, framework interfacing with a CI / CD pipeline that can integrate the assemblage of software components that collectively automate the building, testing, and delivery of applications within various hosting environments. Also described herein are methods utilizing the aforementioned systems.

The application relates to the technical field of model configuration, in particular to a software architecture framework configuration and generation method based on UML meta-model extension technology. The application proposes the following scheme: a UML activity diagram is constructed to depict function execution flow, and UML interaction constraint conditions containing time sequence, concurrency, branching and interface constraint are generated from the activity diagram; under the constraint of the interaction constraint, a UML component meta-class is extended, meta-attributes such as framework semantic type, running environment and generation configuration are introduced, and an initial software architecture framework model is constructed; in combination with a component knowledge graph library, an outwardly-biased distribution strategy is adopted to distribute activity nodes to reusable components or newly-built components, and a software architecture framework meeting interaction consistency and generation constraint is generated. The application can improve the traceability, reuse stability and engineering generability of architecture configuration.

The application discloses a kind of incremental semantic analysis integrated development environment systems for SystemVerilog hardware design language, comprising: workspace discovery component, for automatically identifying project list and constructing project boundary;Virtual file system component, for maintaining source path and file identification mapping and tracking file status;Incremental semantic database component, for performing local failure and incremental recalculation after source code changes;Semantic capability component, for providing completion, jump, reference, renaming, semantic highlighting, formatting and other capabilities;Protocol scheduling component, for unified scheduling and returning results to requests, notifications, background tasks.The application can perform real-time semantic processing on Verilog / SystemVerilog code in a continuous editing scenario, reduce the delay caused by full recalculation, and improve hardware design and development efficiency.

The present application relates to a kind of Sketch file analysis and layout conversion method, by structure mapping, style and layout adaptation, layout conversion, reshape element hierarchy, realize the conversion of Sketch file to structured JSON description file.Solve the conversion bottleneck of Sketch design file to low-code platform development, greatly improve the development efficiency and design draft restoration quality, also reserve space for future technology iteration.All algorithm parameters in the present application can be adjusted, with more hatching times, conversion restoration degree will be constantly improved.The conversion result is more in line with programmer thinking, realizes the automatic delivery link, eliminates the design-development fault in traditional development process.Structured data mapping, visual layer is directly mapped to business layer component, greatly reduces the workload of artificial configuration.Expected product iteration cycle is shortened by 40%, greatly improves the development efficiency.Reduce the communication cost between design and development, improve team collaboration efficiency.It has the ability to generate DSL across different development platforms, only need to adapt the mapping protocol of target platform.

The application discloses a code automatic generation method based on a SysML model, belongs to the technical field of computers, and comprises the following steps: 1, according to the SysML specification, performing multi-level model checking on the established SysML model, and ensuring that the SysML model is legal and effective; 2, performing conversion and analysis on the SysML model according to the established model content file and in combination with various views in the model; 3, performing component definition and management; 4, constructing a standardized code mapping template; and 5, performing hierarchical code automatic generation to generate final target language code. The application can unify and cooperate the MBSE and MDA methods, provides a specific means for the realization of the SysML model, effectively reduces the model design and development difficulty, improves the design and development capability of the SysML model in the MBSE method, and guarantees the efficiency and quality of the system model development and realization.

The invention provides an AI-driven supply chain software automatic code generation method, relates to the technical field of supply chain software development, and solves the problems that the current supply chain software development efficiency is low, the manual adjustment cost is high and cross-system integration is difficult. The method comprises the following steps: firstly, acquiring a component template library, wherein a front-end component template and a background interface code template which are packaged by adopting a fixed structure and configurable parameters are stored in the component template library; further acquiring a configuration description file, analyzing configuration parameters, retrieving the component template, injecting the configuration parameters into a configurable parameter position of the component template, and splicing according to a project directory specification to generate a basic code prototype of the supply chain software; and finally, analyzing the service context information of the supply chain by using an AI agent, generating a service logic code, and embedding the service logic code into the basic code prototype to obtain a target code of the supply chain software. According to the method, full-process efficient support from a first edition framework to business logic landing can be provided for supply chain software related to ERP, WMS and MAS.

The invention relates to a method for automatically constructing and releasing a Vue front-end component library based on UMD (Unified Model Description) specification, which comprises the following steps: an automatic script execution step for automatically generating and updating a component entry file of the component library to ensure automatic integration of a new component and avoid artificial omission; the implementation steps of introducing the function module as required allow a user to independently load each component in the component library, so that the loading efficiency and the user experience are improved; yarn is used as a dependency management step of a package management tool, so that the dependency installation speed is increased, and the development environment is optimized; and an integration step of the Nexus warehouse, which is used for automatically publishing the component library and performing security management so as to ensure the controllability and confidentiality of internal use. By applying the technical scheme of the invention, the problems of low component library maintenance efficiency and insufficient safety caused by lack of an automatic construction and release process, manual management of component entry files and an on-demand loading function of internal components in the prior art can be effectively solved.

The application relates to the technical field of data enhancement and system engineering, in particular to a user behavior data enhancement method based on an RFLP-driven large language model. The method comprises the following steps: determining a core driving problem and an expected application scenario of to-be-generated user behavior data, determining a task target, a data structure requirement, a data characteristic requirement, a constraint condition and a non-functional requirement of a large language model data generation system based on the RFLP driving, and coding the requirement specifications into a plurality of functional modules, forming a data generation function set according to the modules, constructing a logic scheme based on "strategy-component-combination" for the system, and converting the logic scheme into an executable scheme, finally controlling the large language model to execute the executable scheme to generate the to-be-generated user behavior data. Therefore, the problem that a prompt word is difficult to guarantee the quality and consistency of generated data is solved, and scientific methodological support is provided for constructing a high-quality, controllable and expandable synthetic user data generation system.

A system (100) for artificial intelligence (AI)-driven enterprise software modernization, the system (100) comprising: a. a user device (102) with a user interface (104) configured to receive legacy software artifacts including source code, configuration files, database schemas, interface definitions and runtime logs; b. a communication network (106) configured to enable data communication between the system's components and with external repositories and deployment environments; c. a processing unit (108) that is operationally connected to the user interface (104) of the user device (102) via the communication network (106), wherein the processing unit (108) is configured to execute an AI-driven software modernization workflow, the processing unit (108) comprising: i. a data input module (110) configured to receive legacy software artifacts via the user interface (104) and generate normalized artifact data; ii. a preprocessing module (112) configured to perform at least one of the syntactic analysis, dependency extraction, deobfuscation and metadata enrichment on the normalized artifact data; iii. a semantic intermediate representation generation module (114) configured to create a unified semantic representation that fuses static code semantics with behavioral information derived from runtime logs, the semantic intermediate representation comprising at least control flow structures, data flow relationships, API contracts, security constraints and performance attributes; iv. an artificial intelligence (AI) transformation module (118) configured to generate modernized software components based on the semantic intermediate representation; v. a validation module (120) configured to perform structural, behavioral and interface contract equivalence between the modernized software components obtained from the AI ​​transformation module (118) and the legacy software artifacts received via the data input module (110), and to transmit validation results to the AI ​​transformation module (118) for iterative correction; vi. an output module (122) configured to receive the validated modernized software components from the validation module (120) and to generate executable modernization artifacts, including source code, deployment descriptions and interface specifications, the artifacts being provided to the user device (102) via the communication interface (106).

The invention discloses a multi-database type adaptation software development method and system based on MyBatis ecology and a medium. The method comprises the steps that a multi-layer architecture system composed of a MyBatis core framework, a MyBatis-Plus extension assembly and a MyBatis-Plus-Join association query assembly is constructed; a universal CRUD interface provided by MyBatis-Plus is dynamically combined through Java business logic codes, and basic database operation is achieved; for a complex business scene, a chain type API of MyBatis-Plus-Join is adopted to realize multi-table association query, and direct compiling of an SQL is avoided; when SQL must be compiled, a multi-version SQL mapping file library is established, and SQL statements corresponding to dialects are dynamically loaded according to the type of an actually deployed database; and the optimal execution scheme is automatically matched through a runtime database type detection module. According to the method, by automatically identifying database dialects, unifying API interfaces and dynamically loading strategies, decoupling of codes and database types is achieved, and development efficiency and system expansibility are remarkably improved.

The invention discloses a binary software component identification method based on multi-modal feature fusion and large model assistance, which belongs to the field of network security, and comprises the following steps of: performing static disassembly on a binary program file to be analyzed to automatically generate assembly language representation for software component analysis; multi-modal information such as a control flow structure, data flow dependence, an instruction sequence and a constant is fused, deep semantic modeling of a target binary system is achieved, and the recognition precision can be remarkably improved; a cross-platform comparative learning mechanism is adopted, so that the same function has unified embedded representation under different architectures, and good architecture robustness and generalization ability are achieved; a semantic abstract described by a natural language is provided for a function by combining the reasoning capability of a large language model, so that the interpretability and the component attribution judgment capability are improved; the method has good automatic analysis capability and adaptability, and can be widely applied to software supply chain traceability, vulnerability dependence propagation detection, code intellectual property compliance analysis and other actual scenes.

The invention provides a semantic modeling-based software demand automatic identification and conversion method and system, and relates to the technical field of software development, and the method comprises the following steps: obtaining a multi-version demand document, and constructing a time sequence semantic representation; deducing a dependency relationship between demand entities and resolving conflicts, and constructing a dependency relationship graph; software components are generated for the demand entities, semantic verification is executed, and root causes are positioned and repaired; establishing a component interaction relationship to form a software architecture; the timing consistency is verified and the dependency inference rule is optimized. According to the method, demand evolution can be automatically tracked, dependency conflicts can be identified, accurate conversion from demands to software architecture is realized, and the software development efficiency and quality are improved.

The application provides an MVP architecture development method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining attribute information of a target module component, and a name and a relative path of a to-be-developed view class; creating an MVP folder under a target module component directory according to the attribute information of the target module component and the name and the relative path of the to-be-developed view class; determining a prefix code of MVP architecture development code according to the name of the to-be-developed view class; and generating the MVP architecture development code of the target module component under the MVP folder according to the prefix code of the MVP architecture development code according to a preset writing specification of the MVP architecture development code. The method provided by the above scheme automatically generates the MVP architecture development code that meets the writing specification of the MVP architecture development code, and the developer does not need to manually write the code, thereby improving the development efficiency of the MVP architecture.

The invention discloses a three-dimensional design software-oriented component attribute dynamic binding method. The method comprises the following steps of: S1, receiving component classification information input by a user; s2, based on a pre-trained language model, converting the element classification name into vector representation; s3, calculating a similarity score between the element classification vector and a plurality of attribute table vectors; s4, recommending the most matched attribute table according to the similarity score; s5, displaying the recommended attribute table for the user to confirm or modify, and obtaining a final attribute table confirmed by the user; and S6, based on the attribute table confirmed by the user, updating the attribute relation graph maintained by the system to record the association strength of the classification and the attribute table. Compared with the prior art, the association process of the element classification and the attribute table is automated through the intelligent algorithm, and the problems of tedious operation, low efficiency, high error rate and poor user experience in the prior art are effectively solved.

The invention relates to the technical field of computer software engineering, and discloses a method and a device for automatically generating scaffold engineering based on an architecture scheme document. The method comprises the following steps: inputting a project architecture design document, analyzing and extracting constraints by adopting a fine-tuning artificial intelligence model, generating a three-dimensional constraint list, performing legality verification on the three-dimensional constraint list, matching a component version in a built-in CBB component library according to the list, automatically associating three-party dependencies, executing dependency conflict detection, and generating a final dependency list. And based on the three-dimensional constraint list and the dependency list, generating a basic engineering code through a code generation engine, integrating prefabricated service logic and operation and maintenance monitoring configuration, and executing automatic test closed-loop verification on the generated complete engineering. According to the method, full-process automatic generation from an architecture document to an operable project can be realized, project initialization efficiency is greatly improved, dependency conflicts are reduced, business development efficiency is improved, and controllable and reliable quality of a delivery project is ensured.

The invention discloses a heterogeneous BIM (Building Information Modeling) model CAE (Computer Aided Engineering) pretreatment conversion method based on civil structure semantic understanding, and belongs to the field of computer aided engineering.The method comprises the following steps: analyzing a heterogeneous BIM file, and extracting geometric topology and component attributes; based on the geometric features, the BIM attributes and the topological relation, the semantics of the civil structure components are intelligently identified and marked; geometric dimensionality reduction, detail elimination and topological optimization are carried out on the recognized component, and a CAE intermediate model with enhanced structural semantics is constructed; and finally, automatically mapping and loading attributes required by CAE analysis, and outputting an analysis model file which can be identified by the target CAE analysis software. According to the method provided by the invention, the automation level and efficiency of BIM-CAE collaboration can be remarkably improved, the problems of BIM data isomerism, semantic mismatching and geometric redundancy are effectively solved, and a key technical support is provided for civil engineering digital transformation.

The invention discloses a third-party open source component detection method and system based on functional module integrity, and belongs to the technical field of software engineering. In order to solve the problem of inaccurate version identification caused by the influence of code obfuscation, optimization and reduction on third-party library detection in the prior art, the technical means of multi-granularity method feature extraction, progressive method matching, functional module construction and library matching, optimal library selection and the like are mainly adopted. According to the method, the robustness of third-party library detection on code obfuscation and optimization can be improved, high-precision library and version recognition is realized, solution of method matching conflicts is supported, and the integrity and accuracy of detection are improved.

The application belongs to the field of software development, and particularly relates to an SPL management method and system based on Scrum architecture and ontology technology, which comprises the following steps: constructing an SPL management system, a manager acquires user stories, adopts an ontology model to match the user stories, generates requirement characteristics, and adds the requirement characteristics to a requirement characteristic to-do list; acquiring a component unique identifier and a component name of the requirement characteristic ontology, searching for matching according to the component unique identifier and the component name in an information base, and generating a requirement matching list; comparing the matching degree of each component of the requirement matching list with a set matching threshold, constructing a project according to the comparison result, and developing a product according to the constructed project; the application takes Scrum architecture and the concept and technology of SPL as the center, focuses on the requirement analysis stage, proposes to use a well-defined unified requirement description specification, reduces large-scale preliminary design, and improves software resource reusability and customizability.

The invention relates to the technical field of interactive design, and discloses a component loading method and system, and the method comprises the following steps: extracting JSON style data of a token warehouse of a design drawing; merging the default configuration, the theme token and the business layer to obtain JSON style data of final configuration; using the JSON style data of the token warehouse and the finally configured JSON style data to update the style data of the component library; packaging the atomic-scale components in the component library subjected to the style data updating into a component dependency package; and the service layer requests the CDN to load the component dependency packet, and loads the atomic-scale components and / or the high-order components combined by the atomic-scale components. According to the invention, the problem of difficulty in direct cross-project reuse in the prior art is solved.

A software package is received and unpacked into a plurality of components. Features are extracted from each component which are indicative (i.e., useful, etc.) in determining whether such component presents a software supply chain risk. The extracted features are consumed by one or more machine learning models to determine a level of supply chain risk associated with the component. This determined level of supply chain risk can be provided to a consuming application or process. Component identities can also be identified using machine learning or other similarity analyses. In some cases, embeddings are used to characterize risk and / or provide component identities. Related apparatus, systems, techniques and articles are also described.

The application provides a software requirement automatic recognition and conversion method and system based on semantic modeling, relates to the technical field of software development, and comprises the following steps: obtaining multiple versions of requirement documents and constructing a time sequence semantic representation; inferring a dependency relationship between requirement entities and resolving conflicts to construct a dependency relationship graph; generating software components for the requirement entities and performing semantic verification, locating a root cause and repairing; establishing a component interaction relationship to form a software architecture; and verifying time sequence consistency and optimizing dependency inference rules. The application can automatically track requirement evolution, recognize dependency conflicts, realize accurate conversion from requirements to a software architecture, and improve software development efficiency and quality.

Some aspects relate to technologies for software development using a component ecosystem with generative artificial intelligence. In accordance with some aspects, natural language text is received for code generation. Based on the natural language text, one or more component specifications are identified, and a prompt is generated from the natural language text and the component specification(s). Each component specification has a corresponding input, a corresponding output, and one or more corresponding properties. Given the prompt, a generative model generates one or more component instances by hydrating one or more properties of the component specification(s). When multiple component instances are generated, the generative model can also determine a control flow logic specifying an order for the component instances, and the generative model can further generate a translation layer between successive component instances.

The application discloses a low-code development platform implementation method, equipment and medium, and the method comprises the following steps: receiving requirements in the form of natural language, sketches and other non-programming languages, using a large language model to analyze and generate a structured design model; in the process of visual development, an intelligent recommendation engine is used to actively recommend components and arrangement schemes, and an AI auxiliary module is used to perform real-time verification and optimization on graphical logic; finally, a pre-trained code generation model is called to output target language source code conforming to enterprise-level specifications. The application realizes intelligent assistance for the whole process from requirement description to code generation, significantly reduces the development threshold, and improves the development efficiency and code quality.

The invention discloses a semantic analysis method and system for version differences of three-dimensional assemblies, and relates to the technical field of computer aided design. The method comprises the following steps: acquiring two version data of a three-dimensional assembly design file; carrying out analysis and lightweight sequence processing on the three-dimensional scene graph to generate a structured text only containing a hierarchical relationship and a component identifier; inputting the structured texts of the two versions into a pre-trained large language model for difference reasoning; and obtaining a natural language change abstract output by the model, and displaying the natural language change abstract in the version comparison view. According to the method, the problem that a traditional geometric comparison tool cannot explain structural and semantic changes is solved, a complex BOM structure is converted into sequence data which can be understood by AI, automatic recognition and summarization of advanced change behaviors such as component movement and hierarchical recombination are achieved, and the efficiency of engineering design review is remarkably improved.

The application discloses a heterogeneous BIM model CAE pretreatment conversion method based on civil structure semantic understanding, and belongs to the field of computer-aided engineering, and the method comprises the following steps: analyzing a heterogeneous BIM file, and extracting geometric topology and component attributes; intelligently identifying and labeling civil structure component semantics based on geometric features, BIM attributes and topological relations; performing geometric dimension reduction, detail elimination and topological optimization on the identified components, and constructing a CAE intermediate model with enhanced structure semantics; and finally automatically mapping and loading the required attributes for CAE analysis, and outputting an analysis model file that can be recognized by a target CAE analysis software. The method provided by the application can significantly improve the automation level and efficiency of BIM-CAE collaboration, effectively solve the problems of BIM data heterogeneity, semantic mismatch and geometric redundancy, and provide key technical support for the digital transformation of civil engineering.