Front-end code automatic alignment and change verification method, system, device and medium

Abstract

The application relates to the technical field of computers, can be applied to financial and medical scenarios, and discloses a front-end code automatic alignment and change verification method, system, device and medium. The method comprises the following steps: constructing a semantic mapping index table of old interface fields and business codes in response to a package management script command; performing interface field level difference comparison on a remote interface protocol and a local historical snapshot to generate a change list; constructing a prompt word based on the index table and the change list, generating an adapter code segment, and non-invasively injecting the business code, updating the index table and the snapshot; and completing consistency verification and controlling submission before submission. The application realizes automatic perception of interface changes, non-invasive adaptation of inventory codes, and submission quality forced verification, and improves front-end engineering efficiency and system stability.

Description

Technical Field

[0001] This application relates to the field of computer technology and can be applied to financial and medical scenarios. Specifically, it relates to a method, system, device, and medium for automatic front-end code alignment and change verification. Background Technology

[0002] In current agile front-end development processes, front-end and back-end collaboration heavily relies on API documentation. When back-end developers change the Application Programming Interface (API) definition, front-end developers need to manually update the corresponding request call code and business logic code. This process has the following significant drawbacks in complex front-end projects: First, the "update silos" of existing code and the dilemma of manual adaptation: Several automated code generation tools have emerged in the industry, such as swagger-js-codegen or yapi-to-typescript. However, these tools generally adopt a "coverage-based generation" mode, meaning they can only generate new request function files (such as api.ts) in a specified output directory for the latest interface definition. However, in real-world front-end projects, developers have already deeply consumed the return values ​​of the interfaces in numerous .vue, .tsx, and .jsx business components, including destructuring assignment, data filtering, field renaming, and two-way form binding—all existing business logic. The "full coverage" mode of existing tools cannot identify and retain this existing code. This means that after backend protocol changes, developers still need to spend a significant amount of time manually searching, adapting, and regression testing every field reference in the business components, which can easily lead to online failures.

[0003] Secondly, there is a lag in the perception of interface changes: When a backend interface undergoes field renaming, data type changes (e.g., from numeric to string), or field silent deletion, the frontend engineering lacks an automated static scanning mechanism to accurately locate all affected business code segments. Due to the lack of an effective and automated "difference-driven" feedback loop, this inconsistency between frontend and backend protocols is often delayed until the integration and debugging phase, or even only exposed during production, leading to emergency rollbacks or overnight fixes, resulting in extremely high software delivery costs.

[0004] Third, there is a lack of non-intrusive automated repair solutions: Existing solutions attempt to directly search and replace variable names in business code using custom scripts. However, this "intrusive" batch modification method is highly susceptible to disrupting normal code formatting, comments, and scope chains, and may inadvertently damage local variables with the same name or unrelated fields. More importantly, for large projects or branches involving multiple collaborators, directly modifying the business source code can trigger numerous code merge conflicts, resulting in extremely high risks in practical implementation.

[0005] Fourth, the lack of quality control before code submission: Existing automated tools are all "one-time generation" tools, their responsibility ending after generating the request code. They cannot enforce verification that fields used in the front-end business code are compatible with the latest interface protocols before developers submit code to a version control system (such as Git). Due to the lack of engineered quality red lines, interface inconsistencies can easily pass through code reviews, eventually flowing into the main branch and being deployed to the production environment. The exposure of this defect is highly random and delayed, severely undermining the reliability and efficiency of software delivery.

[0006] Therefore, there is an urgent need for a lightweight front-end engineering method that can automatically detect interface changes, adapt existing business code non-intrusively, and be seamlessly embedded into existing pre-submission quality control processes to solve the above-mentioned technical problems. Summary of the Invention

[0007] To address the aforementioned issues, this application provides a method, system, device, and medium for automatic front-end code alignment and change verification. By constructing a lightweight automation engine based on the Node.js runtime environment, it automatically loads a protocol snapshot comparator, an association scanner, a glue code synthesizer, and a hook verification module, thereby achieving deep, non-intrusive automatic alignment and change verification between the back-end interface protocol and the existing front-end business code.

[0008] The technical solution adopted in this application is as follows: Firstly, this application provides a method for automatic front-end code alignment and change verification, including: In response to the package management script commands executed by the developer, the abstract syntax tree static analysis is performed on the front-end project source code, the old interface fields used in each business code are tracked, and a semantic mapping index table between the old interface fields and the business code is established. Perform a differential comparison of the latest remote interface protocol document with the local historical interface protocol snapshot at the interface field level to identify each change item in the interface protocol and generate a change list; Based on the semantic mapping index table and change list, construct large language model prompt words, call the large language model to generate adapter code snippets corresponding to each change item, inject each adapter code snippet into the corresponding business code in a non-intrusive manner, and synchronously update the semantic mapping index table and local historical interface protocol snapshot; Before the updated business code is submitted to the version control system, the updated semantic mapping index table is used to perform consistency verification on the updated business code based on the change list. Execute the corresponding commit control logic based on the consistency check results.

[0009] Secondly, this application also provides a front-end code automatic alignment and change verification system, including: The associated scanner is used to perform static analysis of the abstract syntax tree of the front-end project source code in response to the package management script commands executed by the developer, track the old interface fields used in each business code, and establish a semantic mapping index table between the old interface fields and the business code. The protocol snapshot comparator is used to perform differential comparison of the latest remote interface protocol document with the local historical interface protocol snapshot at the interface field level, identify each change item of the interface protocol, and generate a change list. The glue code synthesizer is used to build large language model prompt words based on the semantic mapping index table and change list, call the large language model to generate adapter code snippets corresponding to each change item, inject each adapter code snippet into the corresponding business code in a non-intrusive manner, and synchronously update the semantic mapping index table and local historical interface protocol snapshot. The hook verification module is used to perform consistency verification on the updated business code based on the change list and the updated semantic mapping index table before the updated business code is submitted to the version control system. The commit control module is used to execute the corresponding commit control logic based on the consistency verification results.

[0010] Thirdly, this application also provides an electronic device, 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 implement the steps of the aforementioned front-end code automatic alignment and change verification method.

[0011] Fourthly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the aforementioned front-end code automatic alignment and change verification method.

[0012] The above-mentioned technical solution adopted in this application can achieve the following beneficial effects: The aforementioned front-end code automatically aligns with and verifies methods, systems, devices, and media. Responding to package management script commands executed by developers, it performs static analysis of the front-end project source code using an abstract syntax tree, tracks old interface fields used in various business codes, and establishes a semantic mapping index table between old interface fields and business code. It performs interface field-level differential comparison between the latest remote interface protocol document and local historical interface protocol snapshots, identifies each change to the interface protocol, and generates a change list. Based on the semantic mapping index table and the change list, it constructs large language model prompts, calls the large language model to generate adapter code snippets corresponding to each change, and injects each adapter code snippet into the corresponding business code in a non-intrusive manner, while simultaneously updating the semantic mapping index table and local historical interface protocol snapshots. Before the updated business code is submitted to the version control system, it performs consistency verification on the updated business code using the updated semantic mapping index table based on the change list. Finally, it executes the corresponding commit control logic based on the consistency verification results.

[0013] This application uses package management scripts as a unified entry point, with all configurations distributed along with the project codebase, eliminating the need for developers to install any integrated development environment (IDE) plugins. It automatically builds a semantic mapping index table between existing business code and interface fields, and combines incremental differential comparison to process only the changed fields. Based on this, it automatically generates non-intrusive adapter code snippets and injects them into the business code, without requiring developers to manually modify existing variable names or refactor business logic. Compared to traditional manual verification and global search and replacement methods, this application reduces the interface adaptation work, which originally took hours, to seconds, significantly lowering the manpower costs and refactoring risks associated with front-end and back-end protocol alignment.

[0014] This application establishes a detailed index table that records which files, lines, and variable names reference each interface field throughout the entire project, making interface upgrades of existing code transparent and controllable. For field renaming or type changes, an adapter is injected only at the request layer, without disrupting the original business code structure; for silent field deletion, a deprecation flag is added to the index table for later processing. This design enables large, legacy projects to evolve their interface protocols incrementally and securely.

[0015] Before developers submit code, this application checks each affected old interface field against the change list and the updated semantic mapping index table to ensure it has been adapted or deprecated. Only after all checks pass is the submission allowed. This mechanism, which moves the quality red line forward to before the code leaves the development machine, effectively prevents production environment crashes caused by unhandled interface changes and significantly improves the robustness of the front-end system. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 A flowchart illustrating a front-end code automatic alignment and change verification method according to an embodiment of this application is shown; Figure 2 A schematic diagram of the structure of a front-end code automatic alignment and change verification system according to an embodiment of this application is shown; Figure 3 A schematic diagram of the structure of an electronic device according to an embodiment of this application is shown. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] Figure 1 A flowchart illustrating an embodiment of the front-end code automatic alignment and change verification method according to this application is shown. Figure 1 As shown, this embodiment includes steps S110 to S150: Step S110: In response to the package management script command executed by the developer, perform static analysis of the abstract syntax tree on the front-end project source code, track the old interface fields used in each business code, and establish a semantic mapping index table between the old interface fields and the business code.

[0019] After developers execute the package management (NPM) script command in the front-end project, the command line (CLI) core engine is launched based on the Node.js runtime environment. It automatically loads and wakes up four core functional modules: the associated scanner, the protocol snapshot comparator, the glue code synthesizer, and the hook verification. This provides module scheduling and operation support for the entire process of subsequent interface field semantic mapping, protocol differential comparison, intelligent generation of adaptation code, and code submission consistency verification.

[0020] In some optional implementations, after step S110, in response to the package management script command executed by the developer, the method further includes: parsing the parameters carried by the package management script command and reading the configuration file; wherein the configuration file includes: the access address of the latest remote interface protocol document, the storage path of the local historical interface protocol snapshot, the project path of the front-end project source code, and hook configuration information.

[0021] Package management script commands are automated execution instructions pre-configured in the project's package.json file and executed by developers in the project's terminal. They serve as the starting point for triggering the automatic alignment and change verification process of front-end code, and the entire process can be started by executing standardized script commands.

[0022] When a developer executes the package management script command, the system immediately responds and activates the command-line core engine based on the Node.js runtime environment. The Node.js runtime environment is a common JavaScript runtime environment for front-end projects, providing stable underlying support for operations such as script execution, module loading, file reading and writing, and network requests. The command-line core engine is the core scheduling hub built on top of the Node.js environment, responsible for receiving script commands and parsing command information.

[0023] After the command-line core engine starts, it first parses the parameters carried by the package management script commands and automatically reads the configuration file. The configuration file is a standardized configuration file pre-configured by the developer, which contains four core configuration items: the access address of the latest remote interface protocol document, the storage path of the local historical interface protocol snapshot, the project path of the front-end project source code, and hook configuration information.

[0024] After completing parameter parsing and configuration file reading, the associated scanner, protocol snapshot comparator, glue code synthesizer, and hook verification module are loaded and initialized, completing the deployment of all core functional modules.

[0025] This step uses package management script commands as a unified trigger entry point, relying on the Node.js runtime environment to host the command-line core engine. It centrally manages the access address of the latest remote API protocol documentation, the storage path of local historical API protocol snapshots, the front-end project source code path, and hook configuration information through script parameter parsing and configuration files. This design does not rely on any dedicated integrated development environment plugins or closed-source visualization platforms, featuring lightweight integration and zero environment intrusion. It can be directly distributed and deployed with the code repository, significantly reducing team promotion and environment adaptation costs. Simultaneously, critical paths and validation rules are uniformly incorporated into configuration file management, adapting to the differences in project structures across various projects.

[0026] Semantic mapping of API fields can be achieved through an associated scanner. The entire front-end project source code is read, and abstract syntax tree static analysis technology is used to traverse and perform deep syntax parsing of the source code. This accurately identifies the old API fields actually referenced in the API request call logic and business code within the front-end project. Semantic associations are established between each old API field and its corresponding business code file, line number, variable reference location, etc., ultimately constructing a semantic mapping index table that precisely corresponds to the old API fields and the business code.

[0027] In some optional implementations, step S110 involves performing static analysis of the front-end project source code using an abstract syntax tree to track old interface fields used in each business code and establishing a semantic mapping index table between old interface fields and business code. This includes: retrieving the front-end project source code based on the project path; traversing the front-end project source code to generate an abstract syntax tree; identifying interface request function calls in the front-end project source code based on the abstract syntax tree; analyzing the destructuring assignment pattern of the return value for each interface request function call to track old interface fields used in each business code; and associating the old interface fields with the reference locations in the business code to generate a semantic mapping index table.

[0028] After loading the module, the command-line core engine passes the project path of the front-end project source code from the configuration file to the associated scanner. The associated scanner recursively reads all source code files in the front-end project directory based on this project path, including but not limited to front-end project source code files in formats such as .vue, .tsx, .js, and .ts.

[0029] The associated scanner can call the TypeScript Compiler API to perform global traversal and syntax analysis on the front-end project source code, converting the structured code text into a machine-readable Abstract Syntax Tree (AST). The TypeScriptCompiler API can completely preserve the code's type information, location information, and variable scope information, providing a foundation for subsequent precise field tracing.

[0030] Based on the abstract syntax tree, the definition of the interface request function and the hierarchical call chain are parsed and identified layer by layer, and the entire process logic of the interface request from initiation to data reception is completely sorted out.

[0031] For each identified API request function call, further analysis is performed on the destructuring assignment pattern of its return value to accurately trace all old API fields that are actually referenced and depended upon in each business code.

[0032] For each identified old interface field, the reference location in the business code is also recorded. The reference location can include the file name, line number, function, or component. The old interface fields are semantically associated with their reference locations, generating a semantic mapping index table in .api-map.json format.

[0033] This step utilizes an associated scanner to perform static parsing of the abstract syntax tree of the front-end project source code. It accurately identifies API request function calls and destructuring assignment patterns, automatically tracks all legacy API fields relied upon by the business code, and establishes semantic relationships between these legacy API fields and their reference locations in the business code, generating a standardized `.api-map.json` semantic mapping index table. This approach eliminates the inefficient methods of traditional manual global searches and manual sorting of field references, avoiding manual omissions and mismatches. It provides accurate and reliable underlying index data support for subsequent API protocol comparison, intelligent generation of adaptation code, and consistency verification during the submission phase.

[0034] Step S120: Perform a differential comparison of the latest remote interface protocol document and the local historical interface protocol snapshot at the interface field level to identify each change item of the interface protocol and generate a change list.

[0035] Protocol differential comparison can be achieved using a protocol snapshot comparator. It retrieves the latest remote interface protocol document and simultaneously obtains locally stored historical interface protocol snapshots. A structured differential comparison is performed at the interface field level to accurately identify change types such as field renaming, field type changes, and silent field deletion, thus creating a standardized list of interface changes.

[0036] In some optional implementations, step S120 involves performing a differential comparison of the latest remote interface protocol document and the local historical interface protocol snapshot at the interface field level to identify each change item in the interface protocol and generate a change list. This includes: retrieving the latest remote interface protocol document based on the access address; obtaining the local historical interface protocol snapshot based on the storage path; and using a differential algorithm to perform a field-by-field comparison of the latest remote interface protocol document and the local historical interface protocol snapshot to identify three types of changes: field renaming, field type change, and field silent deletion, forming a structured change list. Among these changes, field renaming and field type change records the mapping relationship between the old and new interface fields, while field silent deletion records the deleted old interface fields.

[0037] After the command-line core engine completes module loading, it passes the access address of the latest remote interface protocol document and the storage path of the local historical interface protocol snapshot from the configuration file to the protocol snapshot comparator. The protocol snapshot comparator initiates a network request based on the access address to retrieve the latest remote interface protocol document. Based on the storage path, the protocol snapshot comparator retrieves the last saved local historical interface protocol snapshot from the front-end project's cache directory.

[0038] The protocol snapshot comparator performs structured parsing of the latest remote interface protocol document and local historical interface protocol snapshots, unifying them into a standardized JSON structure. Using interface fields as the smallest comparison granularity, it performs bidirectional differential comparison of each field's name, data type, and obsolete status. During the differential comparison process, it accurately distinguishes and marks three types of changes: field renaming, field type change, and silent field deletion.

[0039] Field renaming means that the name of a certain interface field in the local historical interface protocol snapshot is changed to a different name in the latest remote interface protocol document, while the path, type semantics, etc. in the data structure remain highly similar. For example, changing from "u_name" to "userName".

[0040] A field type change indicates a change in the data type of the same interface field in both the local historical interface protocol snapshot and the latest remote interface protocol document. For example, it might change from "string" to "number".

[0041] Silent deletion of a field means that an interface field that exists in the local historical interface protocol snapshot does not exist in the latest remote interface protocol document, and there is no corresponding interface field.

[0042] For field renaming and field type change types, the identified change items will be associated with the names and types before and after the change; for field silent deletion types, the old interface fields of the identified change items will be marked and uniformly summarized into a structured change list.

[0043] This step compares the latest remote interface protocol document with the local historical protocol snapshot at the interface field level, replacing the inefficient traditional manual check-by-item method. It can automatically and accurately identify various protocol changes such as field renaming, field type changes, and silent field deletion, avoiding the problem that silent changes to the backend interface cannot be detected by the frontend in a timely manner.

[0044] Step S130: Construct large language model prompt words based on semantic mapping index table and change list, call large language model to generate adapter code snippets corresponding to each change item, inject each adapter code snippet into the corresponding business code in a non-intrusive manner, and synchronously update semantic mapping index table and local historical interface protocol snapshot.

[0045] Intelligent adaptation code generation can be achieved through a glue code synthesizer. It reads the semantic mapping index table and change list, and constructs large language model prompts by combining business code context information, interface field change details, and code style constraints. By calling the large language model, it intelligently generates adapter code snippets adapted to each interface change, and then precisely injects these snippets into the affected corresponding business code using a non-intrusive incremental embedding method, without modifying the original business code. After injecting the adapter code snippets, it synchronously updates the semantic mapping index table and local historical interface protocol snapshots, completing the synchronous iteration of interface change adaptation, code injection, and index table and protocol snapshots.

[0046] In some optional implementations, step S130 involves constructing a large language model prompt based on the semantic mapping index table and the change list, calling the large language model to generate adapter code fragments corresponding to each change item, injecting each adapter code fragment into the corresponding business code in a non-intrusive manner, and synchronously updating the semantic mapping index table and the local historical interface protocol snapshot. This includes: traversing each change item in the change list and querying the affected business code in the semantic mapping index table; constructing a large language model prompt based on the change item, the affected business code, and code specification constraints, and calling the large language model to generate adapter code fragments; embedding each adapter code fragment into the corresponding business code in an incremental injection manner; for business code with embedded adapter code fragments: if the corresponding field is renamed or the field type is changed, then an adaptation mark is added to the corresponding old interface field in the semantic mapping index table and a mapping relationship with the new interface field is established; if the corresponding field is silently deleted, then an obsolete mark is added to the corresponding old interface field in the semantic mapping index table; obtaining the updated semantic mapping index table; and overwriting and saving the latest remote interface protocol document as the updated local historical interface protocol snapshot.

[0047] The glue code synthesizer receives the semantic mapping index table generated in step S110 and the change list generated in step S120. It iterates through each change item in the change list and quickly retrieves the reference location of the corresponding affected business code in the semantic mapping index table according to the old interface field in the change item.

[0048] For each change, the glue code synthesizer constructs a structured large language model prompt. This prompt includes the following three core dimensions: Context: Specifies the file type (e.g., Vue3) and line number of the affected business code; Change: Describes the evolution of an interface field, such as the evolution from the old interface field u_name to the changed interface field userName.

[0049] Constraint: Requires the generated adapter code to conform to the project's ESLint specification and outputs patch locations and code snippets in JSON format.

[0050] The glue code synthesizer calls the API interface of a large language model (such as an existing mature large language model), sends the large language model prompts to the large language model, and receives the adapter code snippets for the changes returned by the large language model.

[0051] The glue code synthesizer embeds the corresponding adapter code fragments using a non-intrusive incremental injection strategy based on the identified reference locations of the affected business code.

[0052] For example, if the backend changes u_name (the old interface field) to userName (the changed interface field), the adapter code snippet "const u_name=res.userName||res.u_name" will be automatically inserted.

[0053] After incremental injection is completed, the glue code synthesizer synchronously updates the semantic mapping index table and the local historical interface protocol snapshot.

[0054] For the semantic mapping index table, for both field renaming and field type change types, an adaptation flag is added to the corresponding old interface field in the semantic mapping index table, and an association mapping relationship is established between the old interface field and the new interface field. For the silent field deletion type, an obsolete flag is added to the corresponding old interface field in the semantic mapping index table. This results in the updated semantic mapping index table.

[0055] For local historical interface protocol snapshots, the latest remote interface protocol document is overwritten and saved, and the local historical interface protocol snapshot is iteratively updated to ensure that the updated local historical interface protocol snapshot is consistent with the latest remote interface protocol document.

[0056] This step utilizes a glue code synthesizer to automate the adaptation and synchronous update of interface field changes. By accurately locating affected business code using a semantic mapping index table, and intelligently generating adapter code snippets based on changes and coding style constraints, it injects these snippets into the corresponding business code incrementally and non-intrusively. This avoids the error risks associated with manually modifying existing business code, significantly reducing the manual and time costs of business code adaptation. Updates are made by adding adaptation markers to the semantic mapping index table, establishing mapping relationships between old and new fields, adding obsolete markers, and overwriting local historical interface protocol snapshots. This achieves integrated synchronization of the interface protocol, business adaptation code, and semantic mapping index table, effectively solving the technical problems of low front-end adaptation efficiency, non-standard adaptation, and version asynchrony after backend interface changes.

[0057] Step S140: Before the updated business code is submitted to the version control system, the updated business code is checked for consistency based on the change list using the updated semantic mapping index table.

[0058] Code commit consistency verification can be achieved through the hook verification module. Before committing the updated business code to the version control system (Git), the hook verification module intercepts the code commit process. Based on the change list and the updated semantic mapping index table, it performs consistency verification on the updated business code, verifying whether the interface fields used by the updated business code match the updated semantic mapping index table, ensuring that the updated business code is always aligned with the updated local historical interface protocol snapshot.

[0059] In some optional implementations, step S140 involves performing a consistency check on the updated business code using the updated semantic mapping index table based on the change list before submitting it to the version control system. This includes: when a developer submits updated business code to the version control system, reading the change list and the updated semantic mapping index table based on the hook configuration information; traversing each change item in the change list; if the change item is a field renaming or field type change, checking whether the old interface field has been marked with an adaptation tag and has a mapping relationship with the new interface field in the updated semantic mapping index table; if the change item is a field silent deletion, checking whether the old interface field has been marked with an obsolescence tag in the updated semantic mapping index table; if yes, the consistency check is considered passed; otherwise, the consistency check is considered failed.

[0060] When a developer executes the `git commit` command to submit updated business code to the version control system, the hook verification module is automatically triggered, reading the change list and the updated semantic mapping index table.

[0061] The verification module iterates through each item in the change list. For each change item, the hook verification module performs different check logic based on its type.

[0062] If the change item is a field renaming or field type change, the hook validation module locates the old interface field in the change item, queries the updated semantic mapping index table for the record corresponding to the old interface field, and verifies whether the record has been marked with an adaptation tag and whether a mapping relationship with the new interface field has been established. When both of the above conditions are met, it indicates that the glue code synthesizer has successfully injected the adapter code fragment into the affected business code, achieving a compatible conversion from the old field to the new field and meeting the consistency requirements.

[0063] If the change type is silent field deletion, the hook verification module locates the deleted old interface field, queries the updated semantic mapping index table for the record corresponding to that old interface field, and verifies whether the record has been marked as obsolete. If an obsolete marker has been added, it means that the system has recognized the silent deletion of the old interface field, thus meeting the consistency requirements.

[0064] The consistency check result is passed when all changes in the change list meet the consistency requirements; otherwise, it fails.

[0065] This step introduces a hook verification module before submitting updated business code to the version control system. It leverages the change list and the updated semantic mapping index table to accurately verify and categorize interface changes. For field renaming and type changes, it checks the integrity of adaptation tags and mappings between old and new fields. For silent field deletion, it checks the configuration of obsolete field flags in old interfaces. This automatically filters for non-compliance issues such as missing interface field adaptations, incomplete mappings, and unmarked obsolete fields at the code submission stage, eliminating the need for manual line-by-line verification of the business code's match with the interface protocol. This effectively avoids submitting unqualified code that hasn't completed interface adaptation. By enforcing mandatory pre-submission verification, it ensures consistency constraints on interface protocol changes, adapter code adaptation, and semantic mapping index table flags, reducing program anomalies and rework costs caused by field mismatches in online environments.

[0066] Step S150: Execute the corresponding commit control logic based on the consistency verification result.

[0067] Finally, based on the consistency check results, the system executes the corresponding commit control logic. Specifically, if the consistency check fails, the commit of the updated business code is blocked, and the business code displaying inconsistent fields is shown; if the consistency check succeeds, the commit of the updated business code is allowed.

[0068] During the iterative development of financial industry systems, banks, securities firms, and payment platforms frequently experience changes to their front-end and back-end interfaces, involving the iterative upgrades of sensitive interface fields such as user account information, transaction logs, risk control parameters, and settlement fields. The technical solution proposed in this application can automatically perform snapshot comparison and field-level change identification of financial business interface protocols, construct a semantic mapping index table through static source code analysis, and accurately locate the code locations affected by interface changes in front-end business pages and transaction components such as wealth management, credit, and payment settlement. It automatically generates non-intrusive adapter code through a large language model, achieving compatibility adaptation between old and new interface fields without requiring extensive manual modifications to core financial business logic. Simultaneously, it utilizes hook-based pre-submission verification to enforce consistency between financial business code and interface protocols, preventing production failures such as transaction errors, fund settlement anomalies, and risk control verification failures caused by interface field renaming, type changes, or silent field deletion. This meets the requirements of high stability, high compliance, and low iteration risk in financial systems, adapting to the strict version control, complex business chains, and operational specifications of the financial industry where core business code cannot be arbitrarily modified, ensuring that the entire process of financial interface iteration is traceable, verifiable, and seamlessly adaptable.

[0069] In healthcare IT scenarios, hospital electronic medical record platforms and online consultation platforms involve iterative updates of interface protocols for a large amount of patient information, diagnostic data, laboratory indicators, and prescription fields. Furthermore, the requirements for the standardization, compatibility, and stability of medical data fields are extremely high, prohibiting arbitrary modifications to existing business process code. The technical solution proposed in this application can automatically capture backend medical interface protocols and perform version snapshot differentiation, accurately identifying renaming, type adjustment, and obsolescence / decommissioning changes of fields such as patient name, laboratory indicators, diagnosis codes, and medication fields. Through a semantic mapping index table, it quickly locates frontend business code for electronic medical records, registration and payment, and report queries, intelligently generating adapter code to achieve compatibility and adaptation in a non-intrusive manner, without disrupting the original medical business processing logic and data flow. By utilizing hook consistency checks during the submission phase, it rigorously screens for incompatible or unmarked obsolete medical interface fields, preventing problems such as abnormal medical record loading, incorrect laboratory report display, and failure to transmit diagnostic data due to interface incompatibility. Adapting to the characteristics of the healthcare industry, such as data rigor, high system availability, and controllable version changes, it enables seamless adaptation to changes in medical interfaces and strong verification of code submissions, ensuring smooth iteration of medical information systems and secure and reliable flow of patient data.

[0070] Figure 2 A schematic diagram of the structure of a front-end code automatic alignment and change verification system according to an embodiment of this application is shown. (Refer to...) Figure 2 As shown, the front-end code auto-alignment and change verification system 200 includes: The associated scanner 210 is used to perform static analysis of the abstract syntax tree of the front-end project source code in response to the package management script command executed by the developer, track the old interface fields used in each business code, and establish a semantic mapping index table between the old interface fields and the business code. Protocol snapshot comparator 220 is used to perform interface field-level differential comparison between the latest remote interface protocol document and the local historical interface protocol snapshot, identify each change item of the interface protocol and generate a change list; The glue code synthesizer 230 is used to build large language model prompt words based on the semantic mapping index table and change list, call the large language model to generate adapter code fragments corresponding to each change item, inject each adapter code fragment into the corresponding business code in a non-intrusive manner, and synchronously update the semantic mapping index table and local historical interface protocol snapshot. The hook verification module 240 is used to perform consistency verification on the updated business code based on the change list and the updated semantic mapping index table before the updated business code is submitted to the version control system. The commit control module 250 is used to execute the corresponding commit control logic based on the consistency verification results.

[0071] In some optional implementations, the system described above also includes a command-line core engine. The command-line core engine is used to: parse the parameters carried by package management script commands and read configuration files; wherein the configuration files include: the access address of the latest remote interface protocol document, the storage path of local historical interface protocol snapshots, the project path of the front-end project source code, and hook configuration information.

[0072] In some alternative implementations, in the above system, the associated scanner 210 is used to: retrieve the front-end project source code according to the project path; traverse the front-end project source code and generate an abstract syntax tree; based on the abstract syntax tree, identify the interface request function calls in the front-end project source code; for each interface request function call, analyze the destructuring assignment pattern of the return value to track the old interface fields used in each business code; associate the old interface fields with the reference position of the business code where they are located to generate a semantic mapping index table.

[0073] In some optional implementations, in the above system, the protocol snapshot comparator 220 is used to: retrieve the latest remote interface protocol document based on the access address; obtain local historical interface protocol snapshots based on the storage path; and use a differential algorithm to compare the latest remote interface protocol document and the local historical interface protocol snapshots one by one at the interface field level to identify three types of changes: field renaming, field type change, and field silent deletion, forming a structured change list; wherein, for field renaming and field type change, the mapping relationship between the old and new interface fields is recorded, and for field silent deletion, the deleted old interface fields are recorded.

[0074] In some optional implementations, in the above system, the glue code synthesizer 230 is used to: traverse each change item in the change list and query the affected business code in the semantic mapping index table; construct large language model prompts based on the change item, the affected business code, and code specification constraints, and call the large language model to generate adapter code fragments; embed each adapter code fragment into the corresponding business code in an incremental injection manner; for business code with embedded adapter code fragments: if the corresponding field is renamed or the field type is changed, add an adaptation mark to the corresponding old interface field in the semantic mapping index table and establish a mapping relationship with the new interface field; if the corresponding field is silently deleted, add an obsolete mark to the corresponding old interface field in the semantic mapping index table; obtain the updated semantic mapping index table; and overwrite and save the latest remote interface protocol document as an updated local historical interface protocol snapshot.

[0075] In some optional implementations, in the above system, the hook verification module 240 is used to: when it detects a developer's submission of updated business code to the version control system, read the change list and the updated semantic mapping index table according to the hook configuration information; traverse each change item in the change list; if the change item is a field renaming or field type change, check whether the old interface field has been marked with an adaptation tag and a mapping relationship with the new interface field has been established in the updated semantic mapping index table; if the change item is a field silent deletion, check whether the old interface field has been marked with an obsolescence tag in the updated semantic mapping index table; if yes, the consistency verification is deemed to have passed; if no, the consistency verification is deemed to have failed.

[0076] In some optional implementations, in the above system, the submission control module 250 is used to: if the consistency check fails, intercept the submission of the updated business code and display the business code with inconsistent fields; if the consistency check passes, allow the submission of the updated business code.

[0077] It should be noted that the aforementioned front-end code auto-alignment and change verification system 200 can implement all of the aforementioned front-end code auto-alignment and change verification methods, which will not be elaborated further.

[0078] Figure 3 This invention illustrates a schematic diagram of the structure of an electronic device according to an embodiment of the present application. Figure 3As shown, the electronic device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing 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 databases. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used for communication with external devices via a network connection. When the computer program is executed by the processor, it implements the functions or steps of the front-end code automatic alignment and change verification method.

[0079] In one embodiment, the electronic device provided in this application includes a memory and a processor. The memory stores a database and a computer program that can run on the processor. When the processor executes the computer program, it implements the steps of the aforementioned front-end code automatic alignment and change verification method.

[0080] The above is as stated in this application. Figure 2 The method for automatic front-end code alignment and change verification system execution disclosed in the illustrated embodiments can be applied to a processor or implemented by a processor. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by software instructions. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The steps of the method disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0081] In one embodiment, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the aforementioned front-end code automatic alignment and change verification method.

[0082] It should be noted that the functions or steps that the above-mentioned electronic devices or computer-readable storage media can achieve can be referred to the relevant descriptions in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0083] 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. When executed, the computer program 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), Synchlink, DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0084] 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 system can be divided into different functional units or modules to complete all or part of the functions described above.

[0085] It should be noted that any AI models, software tools, or components not belonging to this company appearing in the embodiments of this application are merely illustrative examples and do not represent actual use. All user personal information involved in the embodiments of this application has been authorized (with the knowledge and consent) by the relevant parties or has been fully authorized by all parties, and the executing entity may obtain it through various legal and compliant means. The collection, storage, use, processing, transmission, provision, and disclosure of the information, data, and signals involved all comply with relevant laws and regulations and do not violate public order and good morals.

[0086] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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. Such 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 this application, and should all be included within the protection scope of this application.

Claims

1. A method for automatic front-end code alignment and change verification, characterized in that, include: In response to the package management script commands executed by the developer, the abstract syntax tree static analysis is performed on the front-end project source code, the old interface fields used in each business code are tracked, and a semantic mapping index table between the old interface fields and the business code is established. Perform a differential comparison of the latest remote interface protocol document with the local historical interface protocol snapshot at the interface field level to identify each change item in the interface protocol and generate a change list; Based on the semantic mapping index table and the change list, construct large language model prompt words, call the large language model to generate adapter code snippets corresponding to each of the change items, inject each of the adapter code snippets into the corresponding business code in a non-intrusive manner, and synchronously update the semantic mapping index table and the local historical interface protocol snapshot; Before the updated business code is submitted to the version control system, the updated business code is used to perform a consistency check based on the change list and the updated semantic mapping index table. Execute the corresponding commit control logic based on the consistency check results.

2. The front-end code automatic alignment and change verification method according to claim 1, characterized in that, Following the package management script command executed by the developer, the following is also included: Parse the parameters carried by the package management script command and read the configuration file; wherein, the configuration file includes: the access address of the latest remote interface protocol document, the storage path of the local historical interface protocol snapshot, the project path of the front-end project source code, and hook configuration information.

3. The front-end code automatic alignment and change verification method according to claim 2, characterized in that, The process of performing static abstract syntax tree analysis on the front-end project source code, tracking old interface fields used in various business codes, and establishing a semantic mapping index table between the old interface fields and the business code includes: Retrieve the front-end project source code according to the project path; Traverse the source code of the aforementioned front-end project to generate an abstract syntax tree; Based on the abstract syntax tree, identify the interface request function calls in the front-end project source code; For each of the aforementioned interface request function calls, analyze the destructuring assignment pattern of the return value to trace the old interface fields used in each of the aforementioned business codes; The semantic mapping index table is generated by associating the old interface fields with the reference locations in the business code.

4. The front-end code automatic alignment and change verification method according to claim 2, characterized in that, The step of performing a differential comparison of the latest remote interface protocol document with local historical interface protocol snapshots at the interface field level to identify each change item in the interface protocol and generate a change list includes: Retrieve the latest remote interface protocol document based on the access address; Obtain the local historical interface protocol snapshot according to the storage path; A differential algorithm is used to compare the latest remote interface protocol document and the local historical interface protocol snapshot at the interface field level to identify three types of changes: field renaming, field type change, and field silent deletion, forming a structured change list. Among them, the field renaming and field type change records the mapping relationship between the old and new interface fields, and the field silent deletion records the deleted old interface fields.

5. The front-end code automatic alignment and change verification method according to claim 1, characterized in that, The process of constructing large language model prompts based on the semantic mapping index table and the change list, calling the large language model to generate adapter code snippets corresponding to each change item, injecting each adapter code snippet into the corresponding business code in a non-intrusive manner, and synchronously updating the semantic mapping index table and the local historical interface protocol snapshot includes: Iterate through each of the change items in the change list and query the affected business code in the semantic mapping index table; Based on the changes, the affected business code, and code style constraints, the large language model prompt words are constructed, and the large language model is called to generate the adapter code snippet; Each of the adapter code fragments is embedded into the corresponding business code using incremental injection. For the business code that has the adapter code fragment embedded, if the field is renamed or the field type is changed, an adaptation tag is added to the old interface field in the semantic mapping index table and a mapping relationship with the new interface field is established; if the field is silently deleted, an obsolete tag is added to the old interface field in the semantic mapping index table; the updated semantic mapping index table is obtained. The latest remote interface protocol document is overwritten and saved as an updated snapshot of the local historical interface protocol.

6. The front-end code automatic alignment and change verification method according to claim 2, characterized in that, Before the updated business code is submitted to the version control system, a consistency check is performed on the updated business code based on the change list and the updated semantic mapping index table, including: When the system detects that a developer has committed updated business code to the version control system, it reads the change list and the updated semantic mapping index table based on the hook configuration information. Iterate through each of the change items in the change list; If the change is a field renaming or a field type change, check whether the old interface field has been marked with an adaptation tag and has a mapping relationship with the new interface field in the updated semantic mapping index table; If the change is a silent deletion of the field, check whether the old interface field has been marked as obsolete in the updated semantic mapping index table; If so, the consistency check is considered passed; If not, the consistency check is deemed to have failed.

7. The front-end code automatic alignment and change verification method according to claim 1, characterized in that, The step of executing the corresponding commit control logic based on the consistency verification result includes: If the consistency check fails, the submission of the updated business code is intercepted, and the business code with inconsistent fields is displayed. If the consistency check passes, the submission of the updated business code is permitted.

8. A front-end code automatic alignment and change verification system, characterized in that, include: The associated scanner is used to perform static analysis of the abstract syntax tree of the front-end project source code in response to the package management script commands executed by the developer, track the old interface fields used in each business code, and establish a semantic mapping index table between the old interface fields and the business code. The protocol snapshot comparator is used to perform differential comparison of the latest remote interface protocol document with the local historical interface protocol snapshot at the interface field level, identify each change item of the interface protocol and generate a change list. The glue code synthesizer is used to construct large language model prompt words based on the semantic mapping index table and the change list, call the large language model to generate adapter code fragments corresponding to each of the change items, inject each of the adapter code fragments into the corresponding business code in a non-intrusive manner, and synchronously update the semantic mapping index table and the local historical interface protocol snapshot. The hook verification module is used to perform consistency verification on the updated business code based on the change list and the updated semantic mapping index table before the updated business code is submitted to the version control system. The commit control module is used to execute the corresponding commit control logic based on the consistency verification results.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the front-end code automatic alignment and change verification method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the front-end code automatic alignment and change verification method as described in any one of claims 1 to 7.

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