Method for generating software process document and electronic device

Abstract

The application provides a software process document generation method and an electronic device, and relates to the technical field of computers. The method comprises the following steps: based on a document generation requirement, using a retrieval enhancement generation technology to retrieve and acquire retrieval information corresponding to the document generation requirement from a preset retrieval enhancement generation knowledge base through a semantic understanding engine; according to a document generation engine, analyzing a target software process document template, acquiring structure mapping information, and filling the retrieval information corresponding to the document generation requirement into the target software process document template according to the structure mapping information to generate an initial software process document; and according to a compliance verification engine, performing compliance verification and rule matching on the initial software process document, and outputting a target software process document that passes the verification, so that the target software process document that passes the verification is automatically generated, the generation and verification are integrated, the generation efficiency of the target software process document is improved, and the quality of the target software process document is ensured.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method for generating software process documentation and an electronic device. Background Technology

[0002] In software engineering management, the writing and management of software process documents are crucial for ensuring project compliance, traceability, and reusability. Software process documents refer to the standardized documents generated at each stage of the software development lifecycle, such as requirements specifications, design documents, and test reports.

[0003] In existing technologies, software process documents are mainly generated manually during software development.

[0004] It can be seen that the generation of existing software process documents relies heavily on manual writing, which results in problems such as low writing efficiency, inconsistent quality, and difficulty in ensuring compliance. Summary of the Invention

[0005] The purpose of this application is to address the shortcomings of the prior art by providing a method and electronic device for generating software process documents, which can improve the generation efficiency of target software process documents and ensure the quality of target software process documents.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows:

[0007] In a first aspect, the present invention provides a method for generating software process documentation, the method comprising:

[0008] Obtain the target software process document template and the user-inputted document generation requirements, respectively;

[0009] Based on the document generation requirements, the semantic understanding engine uses retrieval-enhanced generation technology to retrieve the retrieval information corresponding to the document generation requirements from a preset retrieval-enhanced generation knowledge base.

[0010] According to the document generation engine, the target software process document template is parsed to obtain the structural mapping information of the target software process document template, and the retrieval information corresponding to the document generation requirements is filled into the target software process document template according to the structural mapping information to generate the initial software process document;

[0011] Based on the compliance verification engine, the initial software process document is subjected to compliance verification and rule matching, and the target software process document that passes the verification is output.

[0012] In an optional implementation, the step of performing compliance verification and rule matching on the initial software process document according to the compliance verification engine, and outputting a target software process document that has passed the verification, includes:

[0013] Based on the compliance verification engine, the initial software process document is subjected to compliance verification and rule matching, and a compliance verification report is output, which includes modification suggestions for the initial software process document;

[0014] Based on the proposed modifications, the initial software process document is modified, and the target software process document that passes verification is output.

[0015] In an optional implementation, the step of performing compliance verification and rule matching on the initial software process document according to the compliance verification engine includes:

[0016] According to the compliance verification engine, at least one of the following compliance verifications and rule matching are performed on the initial software process document: format specification verification, terminology consistency verification, inter-document logic verification, and compliance verification. The inter-document logic verification is used to check whether the logic between the initial software process document and its associated documents meets preset requirements.

[0017] In an optional implementation, after modifying the initial software process document according to the modification suggestions and outputting the verified target software process document, the method further includes:

[0018] Based on the target software process document, obtain the modification records for the initial software process document;

[0019] The compliance verification engine is iteratively updated based on the modification records of the initial software process document.

[0020] In an optional implementation, the step of retrieving the document generation requirement from a preset retrieval-enhanced generation knowledge base using a semantic understanding engine and retrieval-enhanced generation technology based on the document generation requirement includes:

[0021] The document generation requirement is parsed using a semantic understanding engine to obtain the domain information and generation intent corresponding to the document generation requirement;

[0022] Based on the domain information and generation intent corresponding to the document generation requirements, retrieval enhancement generation technology is used to retrieve the retrieval information corresponding to the generation intent from a preset retrieval enhancement generation knowledge base;

[0023] Based on the stated generation intent, obtain the corresponding retrieval information, and obtain the retrieval information corresponding to the document generation requirement.

[0024] In an optional implementation, the step of retrieving and obtaining retrieval information corresponding to the generation intent from a preset retrieval-enhanced generation knowledge base based on the domain information and generation intent corresponding to the document generation requirement, using retrieval-enhanced generation technology, includes:

[0025] Based on the domain information and generation intent corresponding to the document generation requirements, the corresponding retrieval information is retrieved from the preset retrieval enhancement generation knowledge base using retrieval enhancement generation technology.

[0026] In an optional implementation, the method further includes:

[0027] Multiple sample standard documents are obtained. Each sample standard document is a software process document and is marked with structural mapping information, which includes: generation path, content elements, and logical relationships.

[0028] The document generation engine is trained and obtained based on the multiple sample standard documents.

[0029] In an optional implementation, the method further includes:

[0030] Multiple compliance sample documents are obtained. Each compliance sample document is a software process document and is marked with rule atomicity information. The rule atomicity information includes: rule atom, compliance attribute, and constraint value.

[0031] The compliance verification engine is trained and obtained based on the multiple compliance sample documents.

[0032] In an optional implementation, obtaining the target software process document template includes:

[0033] In response to the selection operation of any software process document template in the software process document template library, the target software process document template is obtained. The software process document template library includes at least one of the following: project summary report template, project plan, software requirements specification template, software design document template, software test document module, and software coding standard template.

[0034] Secondly, the present invention provides a software process document generation apparatus, the generation apparatus comprising:

[0035] The acquisition module is used to acquire the target software process document template and the document generation requirements input by the user, respectively.

[0036] The retrieval module is used to retrieve retrieval information corresponding to the document generation requirements from a preset retrieval-enhanced generation knowledge base using a semantic understanding engine and retrieval-enhanced generation technology, based on the document generation requirements.

[0037] The parsing module is used to parse the target software process document template according to the document generation engine, obtain the structural mapping information of the target software process document template, and fill the retrieval information corresponding to the document generation requirements into the target software process document template according to the structural mapping information to generate an initial software process document;

[0038] The output module is used to perform compliance verification and rule matching on the initial software process document according to the compliance verification engine, and output the target software process document that has passed the verification.

[0039] In an optional implementation, the output module is specifically configured to include:

[0040] Based on the compliance verification engine, the initial software process document is subjected to compliance verification and rule matching, and a compliance verification report is output, which includes modification suggestions for the initial software process document;

[0041] Based on the proposed modifications, the initial software process document is modified, and the target software process document that passes verification is output.

[0042] In an optional implementation, the output module is specifically used to perform at least one of the following compliance checks and rule matching on the initial software process document according to the compliance verification engine: format specification check, terminology consistency check, inter-document logic check, and compliance check, wherein the inter-document logic check is used to verify whether the logic between the initial software process document and its associated documents meets preset requirements.

[0043] In an optional implementation, the output module is further configured to obtain modification records of the initial software process document based on the target software process document;

[0044] The compliance verification engine is iteratively updated based on the modification records of the initial software process document.

[0045] In an optional implementation, the retrieval module is used to parse the document generation requirement through a semantic understanding engine to obtain the domain information and generation intent corresponding to the document generation requirement;

[0046] Based on the domain information and generation intent corresponding to the document generation requirements, retrieval enhancement generation technology is used to retrieve the retrieval information corresponding to the generation intent from a preset retrieval enhancement generation knowledge base;

[0047] Based on the stated generation intent, obtain the corresponding retrieval information, and obtain the retrieval information corresponding to the document generation requirement.

[0048] In an optional implementation, the retrieval module is used to retrieve corresponding retrieval information from a preset retrieval enhancement generation knowledge base based on the domain information and generation intent corresponding to the document generation requirements, using retrieval enhancement generation technology.

[0049] In an optional implementation, the acquisition module is further configured to acquire multiple sample standard documents, each of which is a software process document and is labeled with structural mapping information, the structural mapping information including: generation path, content elements, and logical associations.

[0050] The document generation engine is trained and obtained based on the multiple sample standard documents.

[0051] In an optional implementation, the acquisition module is further configured to acquire multiple compliance sample documents, each of which is a software process document and is marked with rule atomicity information, the rule atomicity information including: rule atom, compliance attribute, and constraint value;

[0052] The compliance verification engine is trained and obtained based on the multiple compliance sample documents.

[0053] In an optional implementation, the acquisition module is specifically used to include:

[0054] In response to the selection operation of any software process document template in the software process document template library, the target software process document template is obtained. The software process document template library includes at least one of the following: project summary report template, project plan, software requirements specification template, software design document template, software test document module, and software coding standard template.

[0055] In a second aspect, the present invention provides an electronic device, comprising: a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of the software process document generation method as described in any of the foregoing embodiments.

[0056] The beneficial effects of this application are:

[0057] The software process document generation method and electronic device provided in this application include: acquiring a target software process document template and a document generation requirement input by the user; based on the document generation requirement, retrieving retrieval information corresponding to the document generation requirement from a preset retrieval enhancement generation knowledge base using a semantic understanding engine and retrieval enhancement generation technology; parsing the target software process document template according to the document generation engine to obtain the structural mapping information of the target software process document template, and filling the retrieval information corresponding to the document generation requirement into the target software process document template according to the structural mapping information to generate an initial software process document; and performing compliance verification and rule matching on the initial software process document according to a compliance verification engine to output a verified target software process document. This method enables the automatic generation of verified target software process documents based on the target software process document template and the document generation requirement input by the user, achieving integrated generation and verification. Compared with the prior art, this method can improve the generation efficiency of target software process documents and ensure the quality of target software process documents. Attached Figure Description

[0058] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 A system architecture diagram for generating software process documentation is provided in this application embodiment;

[0060] Figure 2 A flowchart illustrating a method for generating software process documentation provided in an embodiment of this application;

[0061] Figure 3 A flowchart illustrating another method for generating software process documentation provided in an embodiment of this application;

[0062] Figure 4 This application provides a schematic diagram of the verification process of a compliance verification engine.

[0063] Figure 5 A flowchart illustrating another method for generating software process documentation provided in an embodiment of this application;

[0064] Figure 6 A flowchart illustrating another method for generating software process documentation provided in an embodiment of this application;

[0065] Figure 7A flowchart illustrating another method for generating software process documentation provided in an embodiment of this application;

[0066] Figure 8 A flowchart illustrating another method for generating software process documentation provided in an embodiment of this application;

[0067] Figure 9 A flowchart illustrating another method for generating software process documentation provided in an embodiment of this application;

[0068] Figure 10 A flowchart illustrating another method for generating software process documentation provided in an embodiment of this application;

[0069] Figure 11 A schematic diagram of the functional modules of a software process document generation device provided in an embodiment of this application;

[0070] Figure 12 This is a schematic diagram of an electronic device structure provided in an embodiment of this application. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0072] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0073] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0074] In related technologies, software process documentation is primarily generated manually during software development. Therefore, the current generation of software process documentation heavily relies on manual writing, resulting in problems such as low efficiency, inconsistent quality, and difficulty in ensuring compliance.

[0075] In view of this, embodiments of this application provide a method for generating software process documents, which can realize intelligent generation and full lifecycle management of software process documents, significantly improve document writing efficiency and quality, reduce document writing time costs, reduce compliance risks, and promote the accumulation and inheritance of organizational knowledge.

[0076] Figure 1 This application provides an embodiment of a software process documentation generation system architecture diagram. Figure 2 This is a flowchart illustrating a method for generating software process documentation, provided in an embodiment of this application. The execution entity of this method can be an electronic device such as a computer, server, or processor, and it can be deployed in a cloud service or a local private deployment to meet different security requirements. Figure 2 As shown, the method includes:

[0077] S101. Obtain the target software process document template and the document generation requirements input by the user.

[0078] Optionally, such as Figure 1 As shown, the target software process document template can be selected by the user from a software process document template library. This library can include multiple software process document templates, such as project summary report templates, project plans, and software requirements specification templates, etc., without limitation. The target software process document template can be any template from these multiple software process document templates.

[0079] In some implementations, users can input document generation requirements through preset web pages, preset applications, preset software, etc. The document generation requirements can be expressed in natural language and can indicate further editing requirements for the target software process document template.

[0080] For example, if the target software process document template is a software requirements specification template, then the user-input document generation requirements could be: 1. Implement two display methods for server anomaly alarms: topology and list. Functions include: monitoring basic server status (online / offline, process / port status), resource metrics (CPU / memory / disk usage, network bandwidth, etc.); 2. Support multiple alarm channels: system pop-ups, SMS, WeChat for Business, etc.; 3. Support alarm level settings, matching different response strategies based on the urgency level. Of course, it should be noted that the specific content of the document generation requirements is not limited to this.

[0081] S102. Based on the document generation requirements, the semantic understanding engine uses retrieval-enhanced generation technology to retrieve the retrieval information corresponding to the document generation requirements from the preset retrieval-enhanced generation knowledge base.

[0082] The semantic understanding engine can be a pre-built engine, such as GPT, ERNIE, ChatGLM, etc., without limitation. The semantic understanding engine is used to automatically identify and extract structured semantic elements from the input document generation requirements.

[0083] The pre-built knowledge base for enhanced retrieval can be a pre-constructed knowledge base about software process documents. In some implementations, it may include: historically archived software process documents (e.g., historically archived software requirements specifications, software design documents, etc.), experience knowledge bases (e.g., accumulated technical solutions, decision records, best practices, frequently asked questions, etc.), industry standards (e.g., software development-related standard documents published by organizations such as ISO, IEEE, and W3C in the transportation industry, industry cases, and professional literature in the relevant transportation field, etc.), etc. There are no limitations here, and they may vary depending on the actual application scenario.

[0084] Optionally, during the specific generation process, a semantic understanding engine can be used to perform semantic context understanding on the document generation requirements and extract structured semantic elements; based on the extracted structured semantic elements, retrieval enhancement generation technology can be used to retrieve the retrieval information corresponding to the document generation requirements from a preset retrieval enhancement generation knowledge base.

[0085] S103. Based on the document generation engine, parse the target software process document template to obtain the structural mapping information of the target software process document template, and fill the target software process document template with the retrieval information corresponding to the document generation requirements according to the structural mapping information to generate the initial software process document.

[0086] Optionally, the document generation engine parses the target software process document template (e.g., parses it into Markdown format, but is not limited to this), and can obtain the structural mapping information of the target software process document template. Based on the structural mapping information of the target software process document template, the search information corresponding to the document generation requirements is filled into the corresponding position in the target software process document template to obtain the initial software process document.

[0087] The structure mapping information of the initial software process document is consistent with the structure mapping information of the target software process document template, and the initial software process document is filled with retrieval information corresponding to the document generation requirements.

[0088] S104. Based on the compliance verification engine, perform compliance verification and rule matching on the initial software process document, and output the target software process document that has passed the verification.

[0089] Optionally, the compliance verification engine can extract the rule atomicity information of the initial software process document. Based on the rule atomicity information of the initial software process document, it can perform compliance verification and rule matching on the initial software process document to check the compliance, readability, completeness, etc. of the software process document to be verified, and output the target software process document that has passed the verification.

[0090] It should be noted that, furthermore, the target software process document can also be exported. The export format can be a table, text, image, etc., which is not limited here and can be flexibly set according to the actual application scenario.

[0091] In summary, this application provides a method for generating software process documents. The method includes: acquiring a target software process document template and user-inputted document generation requirements; based on the document generation requirements, using a semantic understanding engine and retrieval-enhanced generation technology, retrieving retrieval information corresponding to the document generation requirements from a preset retrieval-enhanced generation knowledge base; according to the document generation engine, parsing the target software process document template to obtain its structural mapping information, and filling the target software process document template with the retrieval information corresponding to the document generation requirements, thereby generating an initial software process document; and according to a compliance verification engine, performing compliance verification and rule matching on the initial software process document, outputting a verified target software process document. This method enables the automatic generation of verified target software process documents based on the target software process document template and user-inputted document generation requirements, achieving integrated generation and verification. Compared to existing technologies, this method improves the efficiency of target software process document generation and ensures the quality of the target software process document.

[0092] Figure 3 This is a flowchart illustrating another method for generating software process documentation provided in an embodiment of this application. In optional implementations, such as... Figure 3 As shown, the above-mentioned compliance verification engine performs compliance verification and rule matching on the initial software process document, and outputs the target software process document that passes the verification, including:

[0093] S301. Based on the compliance verification engine, perform compliance verification and rule matching on the initial software process document, and output a compliance verification report, which includes modification suggestions for the initial software process document.

[0094] In some implementations, the compliance verification engine can extract rule atomicity information from the initial software process document. Based on this rule atomicity information, compliance verification and rule matching can be performed on the initial software process document. If the verification fails, a compliance verification report can be further output. This compliance verification report may include: the total number of issues in the initial software document, the location of each issue, and suggested modifications.

[0095] S302. Based on the modification suggestions, modify the initial software process document and output the target software process document that has passed verification.

[0096] Optionally, based on the modification suggestions, users can check the compliance (whether all boundary conditions are covered) and readability (logic and consistency of generated statements) of each modification suggestion. If the modification suggestions are accepted, in some implementations, the initial software process document can also be modified using a compliance verification engine based on the modification suggestions, and the target software process document that has passed the verification can be output.

[0097] Of course, it should be noted that this application does not limit the specific modification method. Depending on the actual application scenario, you can choose to manually modify some parts and refer to the modification suggestions for others, and let the compliance verification engine automatically complete the modification; or you can choose to have the user manually modify all parts by referring to the modification suggestions. There is no limitation here, and you can set it flexibly according to the actual application scenario.

[0098] By applying the embodiments of this application, a compliance verification engine is used to perform compliance verification and rule matching on the initial software process document, and a corresponding compliance verification report can be output. Based on the compliance verification report, the efficiency of modifying the initial software process document can be improved, and the quality of the initial software process document can be guaranteed.

[0099] Figure 4 This is a schematic diagram of a compliance verification engine provided in an embodiment of this application. In an optional implementation, the above-mentioned compliance verification and rule matching of the initial software process document according to the compliance verification engine includes:

[0100] Based on the compliance verification engine, at least one of the following compliance verifications and rule matching are performed on the initial software process document: format specification verification, terminology consistency verification, inter-document logic verification, and compliance verification. Among them, inter-document logic verification is used to check whether the logic between the initial software process document and its related documents meets the preset requirements.

[0101] In some implementations, the compliance verification engine can perform format specification verification, terminology consistency verification, inter-document logic verification, and compliance verification on the initial software process documents. Of course, this application does not limit the specific verification items. Depending on the actual application scenario, all verification items can be verified by default, or the user can specify the verification items for verification. For example, the user can choose to perform format specification verification on the initial software documents.

[0102] Optionally, such as Figure 4As shown, for the initial software process documents, a document verification request can be submitted to call the compliance verification engine for multi-dimensional verification. For example, if all verification items are verified by default, the verification can be divided into two layers. The first layer can include: format specification verification and terminology consistency verification; the second layer can include: inter-document logic verification and compliance verification.

[0103] Among them, such as Figure 4 As shown, for the first layer, format specification verification can be performed first. If the verification fails, the reason for failure can be recorded as a format error. If the verification succeeds, terminology consistency verification can be performed. If the verification fails, the reason for failure can be recorded as a terminology error. If the verification succeeds, document-to-document logic verification can be performed. If the verification fails, the reason for failure can be recorded as a logical defect. If the verification succeeds, compliance verification can be performed (e.g., key compliance verification for external audits). If the verification fails, the reason for failure can be recorded as a missing external audit requirement. If the verification succeeds, the initial software process document can be marked as having passed all verifications.

[0104] It should be noted that during the verification process, a compliance verification report, including modification suggestions, can be output based on the verification results. The process is categorized according to the compliance verification report: if all verification items fail, the user is prompted to make significant modifications (which may include modification suggestions); if some verification items fail, the user is prompted to pay attention to the suggested items (which may also include modification suggestions); if all verification items pass, the target software process document that has passed verification can be output. For the cases where the user is prompted to make significant modifications or to pay attention to the suggested items, the user can modify the initial software process document according to the suggestions, or the compliance verification engine can automatically modify it; this is not limited here. In some implementations, the compliance verification engine can also record the user's modification history for subsequent iterative updates.

[0105] Figure 5 This is a flowchart illustrating another method for generating software process documentation provided in an embodiment of this application. In optional implementations, such as... Figure 5 As shown, after modifying the initial software process document according to the modification suggestions and outputting the verified target software process document, the following steps are also included:

[0106] S501. Based on the target software process document, obtain the modification records for the initial software process document.

[0107] S502. Based on the modification records in the initial software process document, iteratively update the compliance verification engine.

[0108] Optionally, after modifying the initial software process document, a compliance verification engine can be used to perform multiple compliance verifications and rule matching on the modified initial software process document until a target software process document that passes the verification is output.

[0109] During the verification process, for the target software process document that passes verification, a comparison can be made between the target software process document and the initial software process document to obtain the modification records for the initial software process document. These modifications can be made manually by the user, automatically by the compliance verification engine, or through a combination of the compliance verification engine and manual user modification; no specific limitation is set here.

[0110] Based on the modification records of the initial software process documents, the compliance verification engine can also be iteratively updated. Optionally, the modifications may include, but are not limited to: format specifications, terminology consistency specifications, document logic specifications, compliance specifications, and modification specifications for the compliance verification engine, etc., which are not limited here.

[0111] By applying the embodiments of this application, the compliance verification engine can be iteratively updated based on the modification records of the initial software process document, which can improve the reliability and accuracy of the compliance verification engine verification process.

[0112] Figure 6 This is a flowchart illustrating another method for generating software process documentation provided in an embodiment of this application. In optional implementations, such as... Figure 6 As shown, based on document generation requirements, the above-mentioned semantic understanding engine uses retrieval-enhanced generation technology to retrieve the retrieval information corresponding to the document generation requirements from a preset retrieval-enhanced generation knowledge base, including:

[0113] S601. The semantic understanding engine parses the document generation requirements to obtain the domain information and generation intent corresponding to the document generation requirements.

[0114] The semantic understanding engine can automatically identify and extract structured semantic elements from the input document generation requirements. These structured semantic elements may include domain information and generation intent corresponding to the document generation requirements. Of course, in some implementations, the structured semantic elements may also include constraints.

[0115] Optionally, the domain information corresponding to the document generation requirement can indicate specific domain entities or objects involved in the document generation requirement, such as user login function, requirement document, architectural rationality, non-functional requirements, etc., which are not limited here; the generation intent corresponding to the document generation requirement can indicate the core operation type that the user wants to perform in the document generation requirement, such as adding content, validating documents, modifying structure, querying information, etc., which are not limited here; the constraints corresponding to the document generation requirement can indicate the user's additional requirements for the operation execution method or result in the document generation requirement, such as adding in Chapter 3, following the company template standard, focusing on checking performance indicators, etc., which are not limited here.

[0116] Of course, it should be noted that this application does not limit the number of generation intents corresponding to document generation requirements. Depending on the actual application scenario, multiple generation intents may be included. In addition, in some implementations, the semantic understanding engine can also perform hierarchical and segmented expansion and organization based on the generation intents to generate more detailed generation intents.

[0117] S602. Based on the domain information and generation intent corresponding to the document generation requirements, the retrieval enhancement generation technology is used to retrieve the retrieval information corresponding to the generation intent from the preset retrieval enhancement generation knowledge base.

[0118] Optionally, after obtaining the domain information and generation intent corresponding to the document generation requirement, retrieval enhancement generation technology can be used to retrieve the corresponding retrieval information from the preset retrieval enhancement generation knowledge base, combined with the domain information corresponding to the document generation requirement. This achieves the goal of improving the accuracy of retrieval information through domain adaptability.

[0119] S603. Obtain the corresponding search information based on the generation intent, and obtain the search information corresponding to the document generation requirements.

[0120] In some implementations, if the document generation requirement corresponds to multiple generation intentions, the above-described method can be used to retrieve the retrieval information corresponding to each generation intention. Based on the retrieval information corresponding to each generation intention, the retrieval information corresponding to the document generation requirement can be obtained.

[0121] It should be noted that in some implementations, the semantic understanding engine can be trained and obtained by the following method: obtaining multiple sample document generation requirements, each sample document generation requirement is labeled with semantic parsing information, including: generation intent, domain information, and constraints; and training and obtaining the semantic understanding engine through machine learning methods based on the multiple sample document generation requirements.

[0122] Among them, the generation intent corresponding to the sample document generation requirement can indicate the core operation type that the user wants to perform in the sample document generation requirement; the domain information corresponding to the sample document generation requirement can indicate the specific domain entities or objects involved in the sample document generation requirement; and the constraints corresponding to the sample document generation requirement can indicate the additional requirements of the user for the operation execution method or result in the sample document generation requirement.

[0123] Optionally, based on the semantic parsing information of the requirements and annotations of multiple sample documents, a semantic understanding engine can be trained using machine learning methods, enabling the semantic understanding engine to automatically identify and extract structured semantic elements from the input document generation requirements.

[0124] By applying the embodiments of this application and introducing a semantic understanding engine, it is possible to perform deep semantic analysis on the document generation requirements input by the user, identify its true intent, key entities and contextual dependencies, thereby significantly improving the system's accuracy in understanding complex technical requirements. In addition, the structured semantic representation output by the semantic understanding engine can serve as precise input for subsequent retrieval, generation and reasoning modules.

[0125] Figure 7 This is a schematic diagram illustrating the generation of a software process document provided in an embodiment of this application. In an optional implementation, the above-mentioned method, based on the domain information and generation intent corresponding to the document generation requirements, employs retrieval-enhanced generation technology to retrieve retrieval information corresponding to the generation intent from a preset retrieval-enhanced generation knowledge base, including:

[0126] Based on the domain information and generation intent corresponding to the document generation requirements, the corresponding retrieval information is retrieved from the preset retrieval enhancement generation knowledge base using retrieval enhancement generation technology.

[0127] Optionally, such as Figure 7 As shown, in some implementations, the semantic understanding engine parses the document generation requirements and obtains the domain information and generation intent corresponding to the document generation requirements. Then, based on a knowledge graph engine, it automatically identifies and extracts structured triple information from the domain information and generation intent. Based on the extracted triple information, retrieval enhancement generation technology can be used to retrieve corresponding search information from a preset retrieval enhancement generation knowledge base. Applying the embodiments of this application, the introduction of a preset knowledge graph engine can improve the accuracy and structuring of semantic understanding, as well as cross-document and cross-domain knowledge linkage and reasoning capabilities. Through the combination of retrieval enhancement generation technology and a preset retrieval enhancement generation knowledge base, the retrieval process is no longer limited to surface text matching but revolves around the semantic relationships between entities, significantly improving the relevance and accuracy of the content retrieved from the preset retrieval enhancement generation knowledge base.

[0128] Furthermore, it should be noted that in practical applications, the knowledge graph engine can also iteratively update based on the domain information and generation intent corresponding to the document generation requirements, thereby improving the completeness of the knowledge graph engine.

[0129] In some implementations, such as Figure 7 As shown, the document generation engine can parse the target software process document template, obtain the structural mapping information of the target software process document template, and fill the target software process document template with the retrieval information corresponding to the document generation requirements according to the structural mapping information to generate the initial software process document. In addition, depending on the actual application scenario, if the target software process document template is a new template, the document generation engine can also update the software process document template library according to the target software process document template.

[0130] The compliance verification engine can perform compliance verification and rule matching on the initial software process document and output the target software process document that has passed the verification. In addition, depending on the actual application scenario, if the target software process document is obtained by modification, the compliance verification engine can also update the verification rules in some implementations.

[0131] By applying the embodiments of this application, the knowledge graph, software process document template library, verification rules, etc. can be updated during the generation of target software process documents, which can improve the applicability and generalization ability of the method of this application.

[0132] Figure 8 This is a flowchart illustrating another method for generating software process documentation provided in an embodiment of this application. In optional implementations, such as... Figure 8 As shown, the above method also includes:

[0133] S801. Obtain multiple sample standard documents. Each sample standard document is a software process document and is marked with structural mapping information, which includes: generation path, content elements, and logical relationships.

[0134] Optionally, the generation paths marked in each sample standard document can indicate the mapping sequence from project information to document chapters. For example, a generation path could be project function point -> [functional requirements chapter, functional description subsection]; the content elements marked in each sample standard document can indicate the specific content objects and their attributes that need to be filled in at each path node. For example, the functional description subsection needs to be filled in with elements such as operation process, preconditions, and acceptance criteria; the logical relationships marked in each sample standard document can indicate the logical relationships that need to be satisfied between different content elements. For example, the "module design chapter" in the "software design document" must be associated with the "functional requirements chapter" in the "software requirements specification document".

[0135] S802. Train and obtain a document generation engine based on multiple sample standard documents.

[0136] Optionally, based on the structural mapping information of each sample standard document and its annotations, a document generation engine can be trained using machine learning methods. This allows the document generation engine to automatically identify user intent from the input project key information (i.e., the retrieval information corresponding to the document generation requirements), and dynamically fill in content elements and construct logical connections along the generation path, ultimately outputting a structured document that conforms to the specifications.

[0137] Figure 9 This is a flowchart illustrating another method for generating software process documentation provided in an embodiment of this application. In optional implementations, such as... Figure 9 As shown, the above method also includes:

[0138] S901. Obtain multiple compliance sample documents. Each compliance sample document is a software process document and is marked with rule atomicity information. The rule atomicity information includes: rule atom, compliance attribute, and constraint value.

[0139] The rule atoms annotated in each compliance sample document can indicate the smallest, indivisible verification unit decomposed from the compliance sample document. For example, the requirements document must contain a description of preconditions (such as an inspection section).

[0140] The compliance attributes marked on each compliance sample document can indicate the dimensions verified by each rule atom, such as chapter completeness, terminology consistency, and logical dependency; the constraint values ​​marked on each compliance sample document can indicate the specific standards or thresholds that each rule atom needs to meet, such as "must exist", "must be equal to the definition in the glossary", "must be able to find the corresponding item in the design document", etc., which are not limited here.

[0141] S902. Train and obtain a compliance verification engine based on multiple compliance sample documents.

[0142] Optionally, based on the atomic information of each compliance sample document and its labeled rules, a compliance verification engine can be trained using machine learning methods, enabling the compliance verification engine to automatically identify and extract structured, executable verification rules from the input compliance sample documents.

[0143] Figure 10 This is a flowchart illustrating another method for generating software process documentation provided in an embodiment of this application. In optional implementations, such as... Figure 10 As shown, the above method also includes:

[0144] S905. Obtain the sample intent summary statements corresponding to the multiple sample document generation requirements. Each sample document generation requirement is a generation requirement for sample software process documents. The sample intent summary statements are marked with triple information, which includes: head entity, relation, and tail entity.

[0145] Optionally, each sample document generation requirement can correspond to one or more sample intent summary statements, which is not limited here. Each sample intent summary statement can be marked with a head entity, relationship, and tail entity.

[0146] The head entity is used to indicate the core concept or object described in the sample intent summary statement, such as server alarm monitoring function, database connection pool, performance test cases, etc.; the relation is used to indicate the semantic association between the head entity and the tail entity, such as contain, depend, implement, verify; the tail entity is used to indicate another concept or object related to the head entity.

[0147] S906. Generate sample intent summary statements corresponding to the requirements based on multiple sample documents, and train and obtain a preset knowledge graph engine.

[0148] Optionally, based on the intent summary statements and their labeled triple information from multiple samples, a preset knowledge graph engine can be trained using machine learning methods, enabling the knowledge graph engine to automatically identify and extract structured triple information from the input intent summary statements.

[0149] In summary, applying the embodiments of this application can significantly improve document writing efficiency and consistency, reduce manual intervention, achieve true semantic-level dynamic content generation and expansion, complete generation and verification in an integrated manner, reduce tool switching costs, support organizational knowledge accumulation and personalized adaptation, and improve document quality and compliance.

[0150] Figure 11 This is a functional module diagram of a software process documentation generation device provided in an embodiment of this application. The basic principle and technical effects of this device are the same as those of the corresponding method embodiments described above. For the sake of brevity, parts not mentioned in this embodiment can be referred to the corresponding content in the method embodiments. Figure 11 As shown, the generating apparatus includes:

[0151] The acquisition module 110 is used to acquire the target software process document template and the document generation requirements input by the user, respectively.

[0152] The retrieval module 120 is used to retrieve retrieval information corresponding to the document generation requirements from a preset retrieval enhancement generation knowledge base using a semantic understanding engine and retrieval enhancement generation technology, based on the document generation requirements.

[0153] The parsing module 130 is used to parse the target software process document template according to the document generation engine, obtain the structural mapping information of the target software process document template, and fill the retrieval information corresponding to the document generation requirements into the target software process document template according to the structural mapping information to generate an initial software process document.

[0154] The output module 140 is used to perform compliance verification and rule matching on the initial software process document according to the compliance verification engine, and output the target software process document that has passed the verification.

[0155] In an optional implementation, the output module 140 is specifically configured to include:

[0156] Based on the compliance verification engine, the initial software process document is subjected to compliance verification and rule matching, and a compliance verification report is output, which includes modification suggestions for the initial software process document;

[0157] Based on the proposed modifications, the initial software process document is modified, and the target software process document that passes verification is output.

[0158] In an optional implementation, the output module 140 is specifically used to perform at least one of the following compliance checks and rule matching on the initial software process document according to the compliance verification engine: format specification check, terminology consistency check, inter-document logic check, and compliance check, wherein the inter-document logic check is used to verify whether the logic between the initial software process document and its associated documents meets preset requirements.

[0159] In an optional implementation, the output module 140 is further configured to obtain modification records for the initial software process document based on the target software process document;

[0160] The compliance verification engine is iteratively updated based on the modification records of the initial software process document.

[0161] In an optional implementation, the retrieval module 120 is used to parse the document generation requirement through a semantic understanding engine to obtain the domain information and generation intent corresponding to the document generation requirement;

[0162] Based on the domain information and generation intent corresponding to the document generation requirements, retrieval enhancement generation technology is used to retrieve the retrieval information corresponding to the generation intent from a preset retrieval enhancement generation knowledge base;

[0163] Based on the stated generation intent, obtain the corresponding retrieval information, and obtain the retrieval information corresponding to the document generation requirement.

[0164] In an optional implementation, the retrieval module 120 is specifically used to retrieve corresponding retrieval information from a preset retrieval enhancement generation knowledge base based on the domain information and generation intent corresponding to the document generation requirements, using retrieval enhancement generation technology.

[0165] In an optional implementation, the acquisition module 110 is further configured to acquire multiple sample standard documents, each of which is a software process document and is labeled with structural mapping information, the structural mapping information including: generation path, content elements, and logical associations.

[0166] The document generation engine is trained and obtained based on the multiple sample standard documents.

[0167] In an optional implementation, the acquisition module 110 is further configured to acquire multiple compliance sample documents, each of which is a software process document and is marked with rule atomicity information, the rule atomicity information including: rule atom, compliance attribute, and constraint value;

[0168] The compliance verification engine is trained and obtained based on the multiple compliance sample documents.

[0169] In an optional implementation, the acquisition module 110 is specifically used to acquire a target software process document template in response to a selection operation of any software process document template in the software process document template library. The software process document template library includes at least one of the following: project summary report template, project plan, software requirements specification template, software design document template, software test document module, and software coding standard template.

[0170] The above-described device is used to execute the method provided in the foregoing embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

[0171] These modules can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more microprocessors, or one or more Field Programmable Gate Arrays (FPGAs). Alternatively, when a module is implemented using processing element scheduler code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together as a system-on-a-chip (SOC).

[0172] Figure 12 This is a schematic diagram of an electronic device provided in an embodiment of this application. This electronic device can be integrated into a software process document generation device. For example... Figure 12 As shown, the electronic device may include a processor 210, a storage medium 220, and a bus 230. The storage medium 220 stores machine-readable instructions executable by the processor 210. When the electronic device is running, the processor 210 communicates with the storage medium 220 via the bus 230, and the processor 210 executes the machine-readable instructions to perform the steps of the above method embodiment. The specific implementation and technical effects are similar and will not be described in detail here.

[0173] Optionally, this application also provides a storage medium storing a computer program, which, when run by a processor, executes the steps of the above-described method embodiments. The specific implementation and technical effects are similar and will not be repeated here.

[0174] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0175] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0176] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in a combination of hardware and software functional units.

[0177] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0178] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0179] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need further definition and explanation in subsequent figures. The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for generating software process documentation, characterized in that, The method includes: Obtain the target software process document template and the user-inputted document generation requirements, respectively; Based on the document generation requirements, the semantic understanding engine uses retrieval-enhanced generation technology to retrieve the retrieval information corresponding to the document generation requirements from a preset retrieval-enhanced generation knowledge base. According to the document generation engine, the target software process document template is parsed to obtain the structural mapping information of the target software process document template, and the retrieval information corresponding to the document generation requirements is filled into the target software process document template according to the structural mapping information to generate the initial software process document; Based on the compliance verification engine, the initial software process document is subjected to compliance verification and rule matching, and the target software process document that passes the verification is output. Based on the document generation requirement, the process involves using a semantic understanding engine and retrieval-enhanced generation technology to retrieve the corresponding search information from a pre-defined retrieval-enhanced generation knowledge base, including: The document generation requirement is parsed using a semantic understanding engine to obtain the domain information and generation intent corresponding to the document generation requirement; The knowledge graph engine automatically identifies and extracts structured triple information based on the domain information and the generation intent. Based on the extracted triple information, the retrieval enhancement generation technology is used to retrieve the retrieval information corresponding to the generation intent from the preset retrieval enhancement generation knowledge base. The triple information includes: head entity, relation, and tail entity. Based on the generation intent, obtain the corresponding retrieval information, and obtain the retrieval information corresponding to the document generation requirement; The method further includes: Multiple sample standard documents are obtained. Each sample standard document is a software process document and is marked with structural mapping information. The structural mapping information includes: generation path, content elements, and logical relationships. The generation path marked in each sample standard document indicates the mapping sequence from project information to document chapters. The content elements marked in each sample standard document indicate the specific content objects and their attributes that need to be filled in at each path node. The logical relationships marked in each sample standard document indicate the logical relationships that need to be satisfied between different content elements. The document generation engine is trained and obtained based on the multiple sample standard documents.

2. The method according to claim 1, characterized in that, The process of performing compliance verification and rule matching on the initial software process document based on the compliance verification engine, and outputting the target software process document that has passed the verification, includes: Based on the compliance verification engine, the initial software process document is subjected to compliance verification and rule matching, and a compliance verification report is output, which includes modification suggestions for the initial software process document; Based on the proposed modifications, the initial software process document is modified, and the target software process document that passes verification is output.

3. The method according to claim 2, characterized in that, The compliance verification and rule matching of the initial software process document based on the compliance verification engine includes: According to the compliance verification engine, at least one of the following compliance verifications and rule matching are performed on the initial software process document: format specification verification, terminology consistency verification, inter-document logic verification, and compliance verification. The inter-document logic verification is used to check whether the logic between the initial software process document and its associated documents meets preset requirements.

4. The method according to claim 2, characterized in that, After modifying the initial software process document according to the modification suggestions and outputting the verified target software process document, the process further includes: Based on the target software process document, obtain the modification records for the initial software process document; The compliance verification engine is iteratively updated based on the modification records of the initial software process document.

5. The method according to claim 1, characterized in that, The method further includes: Multiple compliance sample documents are obtained. Each compliance sample document is a software process document and is marked with rule atomicity information. The rule atomicity information includes: rule atom, compliance attribute, and constraint value. The compliance verification engine is trained and obtained based on the multiple compliance sample documents.

6. The method according to any one of claims 1-5, characterized in that, The document template for obtaining the target software process includes: In response to the selection operation of any software process document template in the software process document template library, the target software process document template is obtained. The software process document template library includes at least one of the following: project summary report template, project plan, software requirements specification template, software design document template, software test document module, and software coding standard template.

7. An electronic device, characterized in that, include: The device includes a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of the method for generating software process documentation as described in any one of claims 1-6.

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