Standardized document automatic generation method for software development

Abstract

The invention relates to the technical field of data processing, and discloses a standardized document automatic generation method for software development, which comprises the following steps: establishing a document template library which comprises a plurality of document templates formulated according to software engineering standards; the method comprises the following steps: acquiring project data based on a project management system, wherein the project data comprises structured project data and unstructured project data; according to a preset rule engine, automatically filling the project data into the document template to generate a standardized project document; and performing version control and dynamic updating on the standardized project document. According to the method, the document generation efficiency and consistency are improved, redundancy and errors in the manual processing process are avoided, and transparent and standardized management of the whole process of project data is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method for automatically generating standardized documents for software development. Background Art

[0002] With the continuous development of the IT services industry, the demand for software projects to be more complex, collaborative, and agile is increasing. In this context, documentation during the software development process, as a crucial component of project delivery, has a direct impact on project quality assessment, phased reviews, and final delivery and acceptance. In actual project implementation, software projects require the generation of various standardized documents, such as Business Requirements Specifications, Software Requirements Specifications, System Architecture Design Specifications, Test Reports, and Project Charters. These documents cover every stage of the software development lifecycle and must reflect the current project status while meeting the requirements of corporate audits and industry regulations.

[0003] However, with existing technologies, most project teams must manually copy and paste project data from tools like Jira, ZenTao, and Git into document templates. This is not only inefficient, but the content often lags behind the actual status, affecting the timeliness and consistency of documents. The lack of a unified template library and automated verification mechanism leads to disorganized document formats across different projects, arbitrary version changes, and the inability to trace content updates. This can easily lead to missed delivery audits and unclear responsibilities. Furthermore, mainstream tools like Confluence and Word documents focus on formatting and version tracking, and are unable to automatically generate compliant project documents based on dynamic data such as code submissions and test case execution results.

[0004] Therefore, it is necessary to design a standardized document automatic generation method for software development to solve the problems existing in current technology. Summary of the Invention

[0005] In view of this, the present invention proposes a method for automatically generating standardized documents for software development, aiming to solve the current problems of low document generation efficiency, serious duplication of work and chaotic version control.

[0006] The present invention proposes a method for automatically generating standardized documents for software development, comprising:

[0007] Establishing a document template library, wherein the document template library includes a plurality of document templates developed according to software engineering standards;

[0008] Acquiring project data based on a project management system, wherein the project data includes structured project data and unstructured project data;

[0009] According to a preset rule engine, the project data is automatically filled into the document template to generate a standardized project document;

[0010] The standardized project documents are version controlled and dynamically updated.

[0011] Furthermore, the document template library includes: requirement document templates, design document templates, development and testing document templates, product document templates and management document templates.

[0012] Furthermore, the rule engine includes:

[0013] Trigger rule engine: used to automatically trigger document generation operations based on events;

[0014] Content generation rule engine: used to dynamically generate document content based on data features;

[0015] Verification rule engine: used to verify the field integrity and format compliance of the document content.

[0016] Furthermore, when the trigger rule engine automatically triggers the document generation operation based on an event, it includes:

[0017] The Webhook events of the project management system are monitored, and a finite state machine model is used to determine whether the state meets the trigger conditions. If multiple events meet the trigger conditions, a weighted polling algorithm is used to prioritize the concurrent events.

[0018] Furthermore, when the content generation rule engine dynamically generates document content according to data features, it includes:

[0019] Structuring the unstructured project data based on natural language processing, including: preprocessing the text, the preprocessing including word segmentation, stop word removal, and stemming;

[0020] Extract business entities based on named entity recognition;

[0021] The text vector features are extracted based on the pre-trained BERT model, and the entities extracted from the text are matched with the preset document template fields based on the semantic matching algorithm based on cosine similarity.

[0022] Furthermore, when the content generation rule engine dynamically generates document content according to data features, it also includes:

[0023] Knowledge graph-assisted entity alignment establishes a mapping relationship between identified business entities and standard domain concepts in the knowledge graph. Text context is modeled based on the Transformer network architecture to capture contextual dependencies. If an entity has multiple matching trends, a voting algorithm analyzes historical matching frequencies and selects the most representative field as the final attribution. Warnings are issued when matching results are insufficiently confident or contain logical conflicts.

[0024] Automatically inject entity content into target locations based on the document template structure.

[0025] Furthermore, when the project data is automatically filled into the document template to generate a standardized project document, the process further includes:

[0026] The field binding relationship between the project data and the document template is defined in JSON or XML format, and supports user-defined field extension.

[0027] Furthermore, version control of the standardized project documents includes: automatically generating version numbers; recording the hash value and change records of each version through blockchain; and using the longest common subsequence algorithm to detect document content differences when comparing the content of the new and old versions.

[0028] Furthermore, dynamic updates include:

[0029] Timed triggering and event-driven, the timed triggering is to generate a document baseline version on a daily basis, and the event-driven is to refresh the document content in real time based on data updates.

[0030] Furthermore, the project management system includes: Jira, ZenTao, Git, SVN, TestRail or Zephyr; the data of the system includes requirement items, task information, code submission records, test cases and defect data.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows: This application constructs a document template library containing multiple types of software engineering standard templates, covering documents in various stages such as requirements, design, testing, and delivery, and realizes the unified collection and analysis of structured and unstructured project data by integrating project management systems such as Jira, ZenTao, and Git. Based on the preset rule engine, the mapping relationship between data and template fields is automatically identified to realize intelligent filling of document content, and combined with the version control mechanism and dynamic update strategy, it ensures that the document is always consistent with the project status. This application improves the efficiency and consistency of document generation, avoids redundancy and errors in manual processing, and realizes transparent and standardized management of the entire process of project data. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0033] Figure 1 A flowchart of a method for automatically generating standardized documents for software development provided by an embodiment of the present invention;

[0034] Figure 2 A flowchart of generating standardized project documents in a method for automatically generating standardized documents for software development provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0035] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0036] See Figure 1-2 As shown, this application proposes a method for automatically generating standardized documents for software development, comprising:

[0037] S100: Establish a document template library, which includes several document templates developed according to software engineering standards.

[0038] S200: Acquire project data from a project management system, where the project data includes structured project data and unstructured project data.

[0039] S300: According to a preset rule engine, the project data is automatically filled into the document template to generate a standardized project document.

[0040] S400: Version control and dynamic update of standardized project documents.

[0041] Specifically, S100 builds a library of document templates covering all stages of the software development lifecycle based on software engineering standards such as GB / T 8567, ISO / IEC 12207, and CMMI. Templates include, but are not limited to, business requirements specifications, user requirements specifications, software requirements specifications, system architecture design specifications, outline design specifications, test reports, and project charters. Each document template defines field names, field types, required field identifiers, and logical structure hierarchies in a structured format (such as XML or JSON), ensuring that generated documents meet project audit and industry standards. S200 establishes data interfaces with project management platforms (such as Jira and ZenTao), source code management systems (such as Git and SVN), and testing platforms (such as TestRail and Zephyr) to automatically extract structured data (such as task IDs, status, progress, and use case results) and unstructured data (such as natural language text, such as requirements descriptions, test conclusions, and design concepts) generated during project execution. This data is subsequently parsed and bound to template fields. In S300, the acquired project data is processed according to a preset rule engine, which includes but is not limited to trigger rules, content generation rules, and verification rules. Among them, the content generation rules use natural language processing (NLP) technology to perform entity recognition and semantic matching on unstructured data, and automatically map the extracted business entities to the corresponding fields in the document template. The trigger rules monitor system events to determine the timing of document generation or update. The verification rules perform compliance checks on document integrity and field formats. The final output is a standardized project document that meets the specification requirements. In S400, version management is performed for each document generation or modification operation, including automatically generating version numbers, recording change summaries, and storing version hash values. Blockchain technology is used to ensure that version data cannot be tampered with. It also supports two update mechanisms: scheduled tasks and event-driven: scheduled tasks can generate baseline document versions daily, and the event-driven mechanism automatically refreshes the document content when the project data changes (such as requirement updates, test result changes), ensuring that the document is always synchronized with the project status.

[0042] It's understandable that by establishing a standardized document template library covering the entire software lifecycle, combining structured and unstructured data within the project management system, and leveraging a rules engine to automatically match and populate data with templates, traditional manual editing can be effectively replaced. By introducing version control and dynamic update mechanisms, real-time document synchronization, standardized output, and fully traceable management are achieved, improving document compilation efficiency and accuracy, reducing the risk of human error, and resolving existing issues such as long document generation cycles, outdated content, chaotic structure, and uncontrollable versions.

[0043] In some embodiments of the present application, the document template library includes: requirement document templates, design document templates, development and testing document templates, product document templates, and management document templates.

[0044] Specifically, requirement document templates are used to describe business and technical requirements in the early stages of a project. Typical templates include the Business Requirements Specification (BRS), User Requirements Specification (URS), and Software Requirements Specification (SRS). These templates define the structural fields for functional and non-functional requirements and support dynamic binding of requirement items to system use cases. Design document templates are used to document system design architecture and functional module implementation plans, including the System Architecture Design Specification, Highlight Design Specification (HLD), Detailed Design Specification (LLD), Database Design Document, and Interface Design Document. These templates support multi-level nested structures and module dependency modeling. Development and testing document templates are used to standardize the outputs of development processes and testing activities, including Source Code Management Specifications, Test Plans, Test Reports, and Defect Reports. They enable field-level association with code submission records and test case execution results. Product documentation templates, including User Manuals, Installation and Deployment Guides, and API Interface Documents, are designed for delivery to end users or deployers. They support automatic extraction and population of functional descriptions, installation steps, and interface protocol content. Management document templates are used for project process management and control, such as the Project Charter, Project Plan, Issue Log, Risk Management Report, Change Control Record, Deliverables List, and Project Summary Report. These templates include process control fields (such as responsible person, status, and timeline) and version evolution tracking. Templates are defined in a structured format and support field expansion, conditional nesting, and data binding rule configuration. They enable unified management of field types, content sources, and entry logic at the template level, ensuring consistent document content format and clear logic across different projects.

[0045] It's understandable that by building a standardized document template library covering the entire software development lifecycle, the documentation process can be transformed from experience-driven to template-driven, achieving unified document structure, standardized field definitions, and clear content sources. This template system improves the automation and consistency of project document generation, reducing delivery audit risks caused by confusing formatting, missing fields, or non-standard descriptions. Furthermore, it provides a highly reusable documentation foundation for different projects, offering excellent scalability and cross-project adaptability, enhancing the standardization, controllability, and engineering of project document management.

[0046] In some embodiments of the present application, the rule engine includes:

[0047] Trigger rule engine: used to automatically trigger document generation operations based on events.

[0048] Content generation rule engine: used to dynamically generate document content based on data characteristics.

[0049] Verification rule engine: used to verify the field integrity and format compliance of document content.

[0050] In some embodiments of the present application, when the triggering rule engine automatically triggers a document generation operation based on an event, the process includes:

[0051] Monitor the Webhook events of the project management system and use the finite state machine model to determine whether the state meets the trigger conditions. If multiple events meet the trigger conditions, use the weighted polling algorithm to prioritize the concurrent events.

[0052] In some embodiments of the present application, when a content generation rule engine dynamically generates document content based on data features, it includes:

[0053] Unstructured project data is structured based on natural language processing, including text preprocessing, which includes word segmentation, stop word removal, and stemming.

[0054] Extract business entities based on named entity recognition.

[0055] The text vector features are extracted based on the pre-trained BERT model, and the entities extracted from the text are matched with the preset document template fields based on the semantic matching algorithm based on cosine similarity.

[0056] In some embodiments of the present application, when the content generation rule engine dynamically generates document content based on data features, it also includes:

[0057] Knowledge graph-assisted entity alignment establishes a mapping relationship between identified business entities and standard domain concepts in the knowledge graph. Text context is modeled based on the Transformer network architecture to capture contextual dependencies. If an entity has multiple matching trends, a voting algorithm analyzes historical matching frequencies and selects the most representative field as the final attribution. Warnings are issued when matching results are insufficiently confident or contain logical conflicts.

[0058] Automatically inject entity content into target locations based on the document template structure.

[0059] Specifically, the trigger rule engine is used to monitor key events in the project life cycle and automatically start the document generation process when the preset trigger conditions are met. This includes the Webhook event monitoring function of project management tools (such as Jira, ZenTao), code repositories (such as Git, SVN), and testing platforms (such as TestRail), combined with the Finite State Machine (FSM) model to determine whether the event state transition meets the generation conditions. For example, when the status of a requirement changes from "draft" to "confirmed", the "Software Requirements Specification" is automatically triggered to be generated. When a branch code is merged into the main trunk "release" branch, the "Version Release Notes" are automatically generated. In the case of concurrent events, the weighted round robin algorithm is used to prioritize the order of task execution.

[0060] Specifically, the content generation rule engine dynamically generates standardized document content based on project data features. This module integrates natural language processing (NLP) capabilities and can perform structured conversion on unstructured text, including text preprocessing (word segmentation, stop word removal, stemming), named entity recognition (NER), and semantic matching. The matching process calculates the similarity between the entity and the template field based on pre-trained language models such as BERT (using the cosine similarity algorithm), and aligns the entities through the knowledge graph. The Transformer model is also introduced to perform context modeling and conflict resolution for complex context semantics. For example, the Voting mechanism is used to select the highest confidence field to improve the accuracy and intelligence of the document content.

[0061] Specifically, the validation rule engine is used to verify the structure and format compliance of the document content before and after it is generated. This module has multiple embedded validation rules, including mandatory field detection, format specification detection, logical integrity verification, etc. For example: verify whether the "Software Requirements Specification" contains key fields such as "Requirement ID" and "Acceptance Criteria", detect whether the version number format complies with the specification (such as "V1.2.0"), and complete the field integrity check through regular expressions and graph structure traversal mechanism to avoid data omissions or logical errors during the document generation process.

[0062] It's understandable that by decoupling and modularizing trigger control, content generation, and compliance verification, a fully automated, intelligent, and configurable document generation rules framework has been constructed. Compared to traditional manually driven document compilation methods, this improves the flexibility and automation of project document generation. It can automatically sense and generate document content in real time based on project data, and automatically perform compliance checks based on document quality standards. This reduces delays, omissions, and consistency issues caused by manual operations, and improves the efficiency, quality, and audit pass rate of document delivery.

[0063] In some embodiments of the present application, when automatically filling project data into a document template to generate a standardized project document, the process further includes:

[0064] The field binding relationship between project data and document templates is defined in JSON or XML format, supporting user-defined field extensions.

[0065] Specifically, during the process of automatically populating project data into document templates to generate standardized project documents, a field binding mechanism is further implemented to establish mappings between project data fields and document template fields. Field binding relationships are defined using a structured configuration format, typically declared in JavaScript Object Notation (JSON) or Extensible Markup Language (XML). This binding configuration file pre-defines field keys, field types, data source paths, and mapping rules. For example, within a template, the field "Requirement Title" can be bound to the field with the path "issue.fields.summary" in the Jira system, and the field "Use Case ID" can be bound to the field with the path "test.id" in the TestRail system. These fields are then parsed and populated using the template engine. To enhance adaptability and scalability, the field binding mechanism supports user-defined field extensions. Users can define new binding rules through a graphical interface or configuration files, dynamically adding specific project fields to the document template structure to adapt to the differentiated needs of different industries, projects, or organizations. Field validation and backtracking capabilities are provided during parsing of the binding configuration, enabling identification of missing fields and formatting errors during document generation to ensure the accuracy and consistency of populated content.

[0066] It's understandable that by using JSON / XML structures to define the binding relationship between project data and template fields, a template-driven data population mechanism is implemented, improving the system's adaptability and configuration flexibility in different project scenarios. Supporting user-defined field extensions enables the template system to not only meet the requirements of pre-set standard documents, but also rapidly respond to changing project field structures, avoiding functional bottlenecks caused by hard-coded limitations. This shift from "fixed templates" to "flexible mapping" improves the configurability, scalability, and usability of the document generation system.

[0067] In some embodiments of the present application, version control for standardized project documents includes automatically generating version numbers. A hash value and change history for each version are recorded on a blockchain. When comparing content differences between the new and old versions, a longest common subsequence algorithm is used to detect document content differences.

[0068] Specifically, each time a document is generated or updated, a document version number is automatically assigned and recorded. The version number uses a multi-segment structure, such as "Vx.yz," where x represents the major version number (schema or template structure-level changes), y represents the minor version number (field rule or content structure adjustments), and z represents the revision number (content fine-tuning or data updates). This version number strategy supports linear management and hierarchical differentiation of version evolution. After each document is generated, the system calculates a hash value of the document content (e.g., using the SHA-256 algorithm) and stores the version number, generation timestamp, hash value, and change summary in a pre-set private blockchain. Blockchain nodes can be deployed on the enterprise intranet or in a trusted evidence storage service, ensuring that the document change history is tamper-proof, trustworthy, and auditable. To support automatic comparison and difference annotation between new and old versions of documents, the Longest Common Subsequence (LCS) algorithm is introduced to calculate differences in document paragraph structure and field content. The algorithm identifies additions, deletions, and modifications within the document, annotates the changes, and generates a difference report for review or merging. Version control can be used in conjunction with scheduled tasks or event triggering mechanisms to achieve periodic archiving of versions and real-time differential synchronization.

[0069] It's clear that through version number generation, blockchain-based trusted evidence storage, and a difference detection mechanism, the orderly evolution and version traceability of project documents throughout their lifecycle are achieved. Blockchain technology ensures tamper-proof and audit-proof document versions. The LCS algorithm accurately detects incremental changes to document content, enhancing the intelligence of version management and the transparency of differences. This reduces management risks associated with version confusion, untraceable modifications, and missed delivery audits.

[0070] In some embodiments of the present application, dynamic updating includes:

[0071] Scheduled triggering and event-driven. Scheduled triggering generates a document baseline version on a daily basis, and event-driven refreshing of document content in real time based on data updates.

[0072] Specifically, through preset scheduling tasks, the document generation process is automatically started at a fixed time period (for example, 2:00 am every day) to form the baseline version of the document for that day. The baseline version serves as a stable reference point in terms of structure and content, recording a complete snapshot of the project's status at that moment, and working with the version control module to generate the corresponding version number and change record. The event-driven mechanism is used to achieve real-time updates of document content. By integrating the Webhook communication interface with the project management platform (such as Jira, Git, TestRail), it monitors the change events of key data in the project in real time (such as requirement status updates, task completion, code merges, test result changes, etc.), and determines whether it is necessary to trigger a partial or overall refresh operation of the corresponding document based on preset rules. This mechanism supports on-demand real-time synchronization of document content to avoid data lag. Scheduled triggering ensures version rhythm consistency and archiving stability, and event-drivenness improves the real-time and dynamic response capabilities of updates.

[0073] It's understandable that the dynamic update mechanism, combining timed triggering with event-driven updates, has enabled the transition of standardized project documentation from "static generation" to "continuous synchronization." The scheduled generation of document baselines ensures standardized version archiving and the traceability of project phase audits. The dynamic refresh mechanism, based on real-time data change events, improves the timeliness and accuracy of document content, avoiding version inconsistencies caused by information lags, manual omissions, or frequent manual updates. This enhances the adaptability and delivery reliability of the document system in complex project environments.

[0074] In some embodiments of the present application, the project management system includes: Jira, ZenTao, Git, SVN, TestRail or Zephyr, and the system data includes requirement items, task information, code submission records, test cases and defect data.

[0075] Specifically, in order to achieve the intelligent generation and dynamic maintenance of standardized project documents, the core data generated during the project operation is integrated and obtained from multiple project management and R&D support platforms. The project management system includes but is not limited to the following tools and platforms: Jira or ZenTao: used to obtain project requirements (such as requirement ID, title, priority, status, acceptance criteria, etc.) and task information (such as task name, person in charge, progress, planned time, dependent tasks, etc.). Git or SVN: used to extract code submission records, including submission ID, submitter, timestamp, change file list, associated requirement ID, code review status, etc. TestRail or Zephyr: used to collect test case data (such as use case ID, step description, expected results, executor, execution status) and defect data (such as defect ID, severity, status, repair record, regression verification information, etc.) in the test platform. By calling the platform's open API interface, various types of data are captured in a structured form and written into a unified data access model, supporting operations such as field mapping, entity binding, and content filling. On this basis, cross-system data association relationships are established, such as binding Jira requirements with Git code submissions, TestRail test cases, and other content through "requirement ID", providing a data foundation for the dynamic generation and version traceability of subsequent document content.

[0076] It is understandable that by integrating mainstream project management and R&D tool platforms, data barriers from requirements management, development process to testing and verification have been broken down, achieving unified collection and centralized processing of data throughout the project life cycle. Through the automated integration of structured requirements information, code change records, and test defect data, the system can dynamically build a complete project data map, effectively supporting the intelligent generation, field filling, and change traceability of standardized documents. Compared with traditional manual collection and manual organization methods, it improves data processing efficiency, reduces information disconnections and omissions, enhances the accuracy, completeness, and auditability of document content, and improves the consistency and professionalism of project delivery documents.

[0077] In the above embodiment, a document template library containing multiple types of standard templates for software engineering is constructed, covering documents at various stages such as requirements, design, testing, and delivery. By integrating project management systems such as Jira, ZenTao, and Git, unified collection and parsing of structured and unstructured project data is achieved. Based on a preset rule engine, the mapping relationship between data and template fields is automatically identified to achieve intelligent filling of document content, and combined with version control mechanisms and dynamic update strategies, it is ensured that the document is always consistent with the project status. This application improves the efficiency and consistency of document generation, avoids redundancy and errors in manual processing, and supports transparent and standardized management of the entire project data process.

[0078] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0079] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0080] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for automatically generating standardized documents for software development, characterized in that: include: Establishing a document template library, wherein the document template library includes a plurality of document templates developed according to software engineering standards; Acquiring project data based on a project management system, wherein the project data includes structured project data and unstructured project data; According to a preset rule engine, the project data is automatically filled into the document template to generate a standardized project document; The standardized project documents are version controlled and dynamically updated.

2. The method for automatically generating standardized documents for software development according to claim 1, characterized in that: The document template library includes: requirement document templates, design document templates, development and testing document templates, product document templates and management document templates.

3. The method for automatically generating standardized documents for software development according to claim 1, characterized in that: The rule engine includes: Trigger rule engine: used to automatically trigger document generation operations based on events; Content generation rule engine: used to dynamically generate document content based on data features; Verification rule engine: used to verify the field integrity and format compliance of the document content.

4. The method for automatically generating standardized documents for software development according to claim 3, characterized in that: When the trigger rule engine automatically triggers a document generation operation based on an event, it includes: The Webhook events of the project management system are monitored, and a finite state machine model is used to determine whether the state meets the trigger conditions. If multiple events meet the trigger conditions, a weighted polling algorithm is used to prioritize the concurrent events.

5. The method for automatically generating standardized documents for software development according to claim 4, characterized in that: When the content generation rule engine dynamically generates document content based on data features, it includes: Structuring the unstructured project data based on natural language processing, including: preprocessing the text, the preprocessing including word segmentation, stop word removal, and stemming; Extract business entities based on named entity recognition; The text vector features are extracted based on the pre-trained BERT model, and the entities extracted from the text are matched with the preset document template fields based on the semantic matching algorithm based on cosine similarity.

6. The method for automatically generating standardized documents for software development according to claim 5, characterized in that: When the content generation rule engine dynamically generates document content according to data features, it also includes: Through knowledge graph-assisted entity alignment, a mapping relationship is established between identified business entities and standard domain concepts in the knowledge graph. The text context is modeled based on the Transformer network architecture to capture contextual dependencies. If an entity has multiple matching tendencies, a voting algorithm is used to analyze historical matching frequencies and select the most representative field as the final attribution. When the matching result confidence is insufficient or there is a logical conflict, an early warning is issued. Automatically inject entity content into target locations based on the document template structure.

7. The method for automatically generating standardized documents for software development according to claim 1, characterized in that: When the project data is automatically filled into the document template to generate a standardized project document, the process further includes: The field binding relationship between the project data and the document template is defined in JSON or XML format, and supports user-defined field extension.

8. The method for automatically generating standardized documents for software development according to claim 1, wherein: Version control of the standardized project documents includes: automatically generating version numbers; recording the hash value and change records of each version through blockchain; and using the longest common subsequence algorithm to detect document content differences when comparing the content of the new and old versions.

9. The method for automatically generating standardized documents for software development according to claim 1, wherein: Dynamic updates include: Timed triggering and event-driven, the timed triggering is to generate a document baseline version on a daily basis, and the event-driven refreshes the document content in real time based on data updates.

10. The method for automatically generating standardized documents for software development according to claim 1, characterized in that: The project management system includes: Jira, ZenTao, Git, SVN, TestRail or Zephyr, and the data of the system includes requirement items, task information, code submission records, test cases and defect data.

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