15 results about "Software documentation" patented technology

The invention relates to code verification, in particular to a code and document consistency reasoning verification system based on a cross-modal logic atlas, which comprises an input layer for receiving source codes and software documents; the feature extraction layer is used for performing feature extraction on the source code and the software document; the abstraction layer is used for converting the extracted features into comparable intermediate representations; the unified modeling layer is used for mapping code logic and document semantics into a unified atlas structure and performing formalized representation by using description logic to obtain a cross-modal logic atlas; the reasoning verification layer is used for performing reasoning verification on the consistency of the code and the document according to the cross-modal logic graph; the result processing layer is used for judging a verification result according to the reasoning verification condition, starting a contradiction positioning mechanism when inconsistency is found, and carrying out contradiction positioning and report generation to obtain an interpretable report; according to the technical scheme provided by the invention, the defects that the consistency between the code and the document is difficult to accurately verify, and accurate contradiction positioning and an interpretable report are difficult to provide can be effectively overcome.

The invention relates to a method for the automated specification of at least one test case (490) for testing software functions of a control unit, comprising the following steps - Creating (S10) a training data set (230), wherein the training data set (230) comprises software documentation, specifications, requirement documents, networking architectures and / or sensor measured values ​​and / or further data of at least one software function of a control unit to be tested; - Training (S20) an AI model (450) with the training data set (230); - entering (S30) first input data (250) for a test case specification and forwarding the first input data (250) to the trained AI model (450); - generating (S40) at least one test case (490) by the AI ​​model (450); - entering (S50) requirements in the form of second input data (270) for optimizing and improving the test case (490); - repeating (S60) the method steps (S40) and (S50) in one iteration until a target test case (495) is reached; - Outputting (S70) the target test case (495) and / or storing the target test case (495) in a database (300).

This invention relates to the field of software development technology and discloses a document processing method, apparatus, device, and medium. The method includes: acquiring multiple heterogeneous data sources of a software project, wherein the heterogeneous data sources include at least source code and software documents associated with the source code; constructing a semantic difference graph describing the semantic relationships between the heterogeneous data sources based on the multiple heterogeneous data sources; assessing the synchronization risk value between the software documents and the current source code based on the semantic difference graph; if the synchronization risk value exceeds a preset threshold, determining the target content in the software documents that needs to be updated synchronously based on the semantic difference graph; generating differential update information for updating the target content based on the current source code and the semantic difference graph; and triggering an update processing flow for the software documents based on the differential update information. This method can be applied to document processing scenarios in fintech and healthcare, improving the accuracy and efficiency of document processing.

The invention discloses a spaceflight control software field-oriented fine tuning data set construction method for a question and answer large model, which comprises the following steps of: firstly, converting all original spaceflight control software documents into structured JSON texts corresponding to chapters, and then carrying out keyword extraction on the structured JSON texts; based on the obtained keywords, generating a question set which is related to the keywords and has clear semantics; next, for the question set, generating a plurality of candidate answers of each question, sorting all the candidate answers of each question, and fusing the candidate answers into a coherent, comprehensive and accurate final answer; and finally, based on each question and the corresponding final answer, constructing a fine tuning data set. The method can achieve the generation of a high-quality question and answer data set in the field of aerospace control software, and supports the fine-tuning training of a large model in the field of aerospace control software.

A serialization processing and retrieval method for spaceflight control software table data belongs to the technical field of aerospace, and comprises the following steps: reading spaceflight control software table data, and representing table elements with placeholders; according to the table data after data cleaning, constructing an LLM input, backfilling the LLM output to a corresponding placeholder, and storing the backfilled table data into a knowledge base; constructing a data set according to the preprocessed table data, and continuing pre-training the LLM on the basis of the data set; and generating a large model retrieval framework according to offline deployment retrieval enhancement of the knowledge base. According to the method, table data in software documents are extracted, large model reasoning is utilized to obtain fusion with original text data to train a field large model, and a retrieval enhancement technology is utilized to improve understanding and application of the large model to table knowledge; and the understanding of software developers on software asset contents borne in a table form in the field of spaceflight embedded control software is improved.

The invention relates to the technical field of data processing, in particular to a translation method of a software development kit, which comprises the following steps of: 1, determining a translation target and a translation range; 2, collecting a terminology library; 3, scanning data, obtaining translation paraphrases and establishing a translation space; step 4, generating a software function component and assembling and verifying complete software; 5, checking and modifying a translation result; and 6, generating a translation report. According to the method, a target software development kit is obtained, a software document, an example code, a configuration tool and a software function requirement document are extracted, a translation database is established, terms, professional nouns and emerging concepts in some specific fields are collected, and then the components are input into a function verification space; and assembling and function verification are performed according to the demand document, so that terms, professional nouns or emerging concepts in specific fields can be accurately translated, and the accuracy and reliability of important information translation results are ensured.

The invention relates to a code defect identification method and system for multi-type feature association and propagation analysis, belongs to the technical field of software testing, and solves the problems of relatively low code defect identification efficiency and relatively small defect identification coverage in the prior art. The method comprises the steps that a software document is analyzed, and multi-type features are generated; generating feature nodes based on the multi-type features, and determining an association relationship between the feature nodes; analyzing the defect case set to generate defect form data; generating defect nodes based on the defect form data; determining an association relationship between the defect node and the feature node; backtracking from the defect node to the feature node by using the determined association relationship, and generating a defect propagation path; the generated defect propagation path is displayed on a software document reading page in an associated mode, judgment information returned by a user for the displayed defect propagation path is obtained, and a code defect recognition result is generated based on the judgment information. Therefore, the code defect identification efficiency is high, and the defect identification coverage range is large.

Aspects of the disclosure relate to a hybrid metaverse environment. A computing platform may synchronize, using edge nodes and with a physical repository server, a soft document repository. The computing platform may receive, via a metaverse application interface, an event processing request. The computing platform may identify, based on the event processing request and using a machine learning model, documents needed to execute the event processing request. The computing platform may update a request queue to identify the event processing request and the documents. The computing platform may access, using an edge node and via the soft document repository, the physical repository server to obtain document images corresponding to the identified documents, and may update a response queue to include the obtained document images. The computing platform may send, to an enterprise user device, a haptic alert indicating that the event processing request is ready for processing.

A document generation platform may include one or more computing devices and / or software hosted on the computing devices. The document generation platform may receive a request for content generation from a user. The document generation platform may perform data collection (e.g., by interfacing with an enterprise system via an application-programming interface (API). The document generation platform may generate a content shell based on the request. The document generation platform may interface with a generative artificial intelligence (AI) server and receive generative AI output. The document generation platform may insert inputs into the content shell, including inputs from the user, the enterprise system, and / or the generative AI server, and perform formatting of each input. The document generation server may finalize the content shell, convert it into a document, and send it to a user.

This disclosure provides a version analysis method based on business architecture, applicable to the field of computer technology. The method includes: acquiring a software document to be tested; extracting a first identifier and a first information technology service from the software document to form a first mapping relationship between the first identifier and the first information technology service; acquiring a code mapping relationship based on a preset association relationship between an information technology architecture model and a business architecture model and the first mapping relationship, wherein the code mapping relationship includes a mapping relationship between the first identifier and the first business architecture model; acquiring a requirement mapping relationship, wherein the requirement mapping relationship includes a mapping relationship between a second identifier and a second business architecture model; and comparing the code mapping relationship and the requirement mapping relationship to calculate a matching rate. This disclosure also provides a version analysis device, equipment, storage medium, and program product based on business architecture.

Various embodiments include methods and systems for automatically evaluating code and / or software documentation for compliance with relevant standards, requirements, and policies. Various embodiments provide a framework for automating compliance reviews of code and / or software against the latest version of standards, requirements, and policies. Methods may include transforming input requests for analysis and code and / or software documents into formats suitable for processing by a large language model (LLM), prompting the LLM to identify concepts and / or elements that are likely subject to a standard, requirement, or policy, submitting a query to a vector database to identify standards, requirements, or policies relevant to the requested analysis and documents, prompting the LLM to determine whether the code and / or software documents comply with each relevant standard, requirement, or policy, and producing a report from of LLM outputs on compliance of the code and / or software documents with each of the relevant standards, requirements, or policies.

The application relates to the technical field of software development, in particular to a conflict detection method based on software collaborative development and related products, wherein an original software model and / or an original software document is uniformly formalized modeling according to a preset structure to obtain a corresponding original unified structure; an operation sequence on the original unified structure is determined according to modification operations of a user on the original software model and / or the original software document; whether each operation action contained in the operation sequence conflicts on the original unified structure is judged; a conflict sequence is determined based on the conflict judgment result of the operation sequence, and the conflict sequence is used to represent a conflict problem existing in the modification operations of the user on the original software model and / or the original software document. The formalized model of the unified structure is constructed, multi-dimensional elements of the software model and the software document are accurately mathematically defined, and the identification precision of model layer conflicts can be effectively improved.

The invention discloses a method for automatically generating a software work product by defining protocol data. The method specifically comprises the following steps: performing formalized representation on a communication protocol; automatically generating a communication protocol processing class source code; independently explaining related contents of the instruction worksheet to complete representation of the human-computer interaction interface; the communication protocol verification software performs mutual verification on the Excel spreadsheet protocol document and the communication protocol through compiling operation, and an interface library function automatically generates an interface with a unified style; and converting the Excel spreadsheet protocol document, and automatically generating a communication protocol description document. According to the method, the protocol processing class C + + source code, the human-computer interaction interface and the verification software can be automatically generated, the software document content is standardized, and the research and development test quality and efficiency are improved.

The invention discloses an embedded software document generation agent construction method based on a large model, and the specific process comprises the steps: knowledge structuring and cue word design: decomposing "General Requirements for Software Development Documents" into a rule set which can be understood and guided by a machine, and designing a cue word template; constructing an intelligent agent framework, and constructing a document generation process by taking task planning and execution as a core; and integrating all modules of the constructed agent framework, and performing closed-loop verification. According to the document generation agent construction method, through intelligent guidance, content generation and quality inspection, the efficiency, accuracy and normalization of software designers for writing software documents according to the standard of General Requirements for Software Development Documents are remarkably improved, and the demand analysis capability is enhanced.

A system for generating a software documentation hierarchy. The system includes an electronic processor. The electronic processor is configured to generate clusters of lower-level artifacts based on natural language descriptions. Each lower-level artifact includes a natural language description. The electronic processor is also configured to, for each cluster, create a higher-level artifact. The higher-level artifact includes a natural language description of the cluster. The electronic processor is further configured to refine the higher-level artifacts containing overlapping information and generate trace links to connect the lower-level artifacts with the higher-level artifacts.