1084results about "Software maintainance/management" patented technology

A data processing system implements obtaining build logs that include information associated with a software build problem; analyzing the logs to generate a knowledge graph identifying the relationship between various entities in the logs; extracting a signature of a candidate root cause of the build problem from the knowledge graph representing a subset of nodes and edges of the knowledge graph; providing the signature of the candidate root cause to a graphical language model to obtain a prediction of a category of root cause failure selected from among a plurality of root cause failures; constructing a prompt for a language model to generate a root cause failure analysis that describes the root cause of the build problem, the prompt including the category of root cause; receiving the root cause failure analysis from the language model; and performing one or more actions in response to receiving the root cause failure analysis.

The invention discloses a method and a system for realizing automatic code generation by using multiple AI Agents, and relates to the field of electric digital data processing, a test driving agent receives a task transmitted by a previous node, and generates a task number, a task description, test data, a unit test script and a code statement; the code generation agent generates or updates codes according to the received task description and code declaration; the test driving agent returns an integrated test script and test data according to the task number; the continuous integration agent performs integration verification and regression test and feeds back information; the test driving agent returns a function test script, a performance test script and test data according to the task number; and the continuous deployment agent carries out continuous delivery and deployment and feeds back information. By means of mutual conversation and cooperative work of multiple AI Agents and in combination with a feedback mechanism, the problem that a single large model cannot complete complex software development tasks is solved, full-process operation automation can be achieved, and the code generation quality and efficiency can be improved.

The invention discloses an AI low-code development component automatic generation method based on a knowledge graph, and relates to the technical field of AI low-code development, and the method comprises the following specific steps: constructing an AI development knowledge graph: constructing a knowledge graph containing a five-layer structure, collecting and preprocessing multi-source data, and extracting various entities and association relationships, so as to obtain an AI development knowledge graph; constructing an ontology structure, importing the ontology structure into a database, and forming a final knowledge graph through manual auditing and machine reasoning optimization; according to the method, the multi-dimensional AI development knowledge graph is constructed, user requirements are analyzed in combination with the optimized natural language processing model, the component configuration scheme is generated by introducing the multi-level reasoning mechanism, and finally the standardized low-code component is automatically generated, so that full-automatic conversion from the user requirements to the low-code component is realized, and the user experience is improved. The defect that an existing low-code platform depends on manual component configuration is overcome, the development period is greatly shortened, and the development cost and the technical threshold are reduced.

The invention provides an operation and maintenance method and device based on a large language model, electronic equipment, a storage medium and a computer program product, relates to the technical field of computers, in particular to the technical field of artificial intelligence large models, natural language understanding and operation and maintenance, and can be applied to operation and maintenance scenes. The specific implementation scheme is as follows: iteratively executing the following operations through an intelligent agent: determining a link operation and maintenance result corresponding to a completed link in an operation and maintenance task; through a large language model, according to the link operation and maintenance result corresponding to the completed link, determining a target tool for continuing to execute the operation and maintenance task from the tool set; and calling the target tool, and generating a link operation and maintenance result corresponding to the next link in the operation and maintenance task. According to the method and the device, the Agent Loop (agent loop) mode is adopted, the target tool of the next link in the operation and maintenance task is determined according to the link operation and maintenance result corresponding to the completed link in the operation and maintenance task, and the applicability of the operation and maintenance scheme in each operation and maintenance scene and the accuracy of the operation and maintenance result are improved.

Systems, methods, and computer program products are provided for providing coding change review. The method includes receiving a code change indicator. The code change indicator is associated with a changed code that has been changed by at least one user. The method also includes determining a coding language of the changed code based on at least one of a keyword library or a code pattern. The method further includes determining a change review indication based on the determined coding language. The change review indicator indicates whether one or more errors exist in the changed code. The method still further includes determining one or more change review actions to carry out based on the change review indication.

The invention discloses an interface element positioning method and device, and the method comprises the steps: obtaining an image when an interface is loaded for the first time, taking the image as a reference image, carrying out the feature extraction and recording of the reference image through a trained element positioning model, and taking the extracted interface element as a reference interface element; acquiring an image when the application runs or the interface is updated and taking the image as a current image, performing feature extraction and recording on the current image by utilizing the trained element positioning model, and taking the extracted interface element as a current interface element; if it is determined that the feature information of the current interface element changes relative to the feature information of the reference interface element, an identification result is output; and according to the identification result, updating the feature information of the reference interface element as the feature information of the current interface element, and updating the corresponding test script to position the interface element. By adopting the method and the device, element positioning can be dynamically identified and adjusted during test operation, and frequent maintenance requirements are reduced.

Disclosed herein are methods and systems to generate code for a workflow. A non-limiting example of a method comprises executing, by a processor, a large language model, which receives an input of an intent associated with a workflow and provides a machine-readable description by: identifying, by searching a hierarchical data structure using a vector embedding associated with the intent, an object corresponding to the intent; identifying a set of data paths within the hierarchical data structure to retrieve the identified object; and generating the machine-readable description, the machine-readable description describing the object and at least one data path within the set of data paths; and generating, by the processor, code for the workflow using the machine-readable description.

The invention provides a multi-rule static detection and large-model dynamic repair method for code defects. The method comprises the steps that code defect types are summarized and abstracted into a unified defect mode rule set; constructing an abstract syntax tree, a control flow diagram and a data flow diagram of the source code; performing static analysis based on a multi-rule engine to identify potential defects; inputting the defect context into a large language model to generate a repair suggestion; performing semantic consistency verification and integration on the repair suggestions; and executing automatic testing and secondary static analysis to verify a repair result. According to the method, the traditional static analysis technology and the modern large language model capability are combined, accurate recognition and intelligent repair of code defects are achieved, a closed-loop defect processing flow is formed, the defect detection accuracy is improved, intelligent repair is achieved, closed-loop verification is formed, the development efficiency is improved, and man-machine cooperation is supported.

The invention provides a security analysis method in a software research and development process. The security analysis method can be applied to the technical field of big data and the technical field of artificial intelligence. The method comprises the following steps: embedding a security analysis plug-in in an integrated development environment; scanning codes written by a user in the integrated development environment in real time through safety rule information preset in the safety analysis plug-in and a heuristic algorithm; identifying a target security problem in response to the security analysis plug-in, marking the target security problem by using the security analysis plug-in, and providing repair suggestion information; and responding to the condition that the user modifies the code based on the repair suggestion information, and utilizing the security analysis plug-in to re-scan the modified code to verify the modification effect.

The invention relates to the technical field of data mining, in particular to a software operation and maintenance method and system. The method comprises the following steps: acquiring engineering simulation heterogeneous hardware data, and performing multi-physics field coupling tensor compression to obtain a multi-physics field topology snapshot; finite element grid nonlinear constraint is executed based on the multi-physics field topology snapshot, and a nonlinear contact strategy tensor is obtained; according to a non-linear contact strategy tensor coding structure dynamics intelligent contract, simulation software dynamics credibility verification is carried out, and a dynamics credible chain is obtained; constructing a hydrodynamic vortex model based on the dynamic trusted chain, and performing boundary layer separation simulation flow optimization on the hydrodynamic vortex model to obtain a vortex flow field map; performing explicit dynamic explicit integration on the vortex flow field atlas to obtain a convergence optimization field; and performing phase field damage evolution according to the convergence optimization field to obtain a multi-physics field evolution twinborn body, and deploying the multi-physics field evolution twinborn body. The method can effectively improve the utilization rate of software computing resources.

To make a meta model as a use destination meta model to be easily used by various systems with the meta model designed by certain system development as a reference source meta model.SOLUTION: A design support system updates a use destination data structure while making a reference source data structure unupdated when a use destination meta model uses a reference source meta model. Since the reference source data structure is made unupdated, the reference source meta model is maintained without changing a content even though the reference source meta model is used. Meanwhile, since the use destination data structure is updated, the use destination meta model can be created again with an updated content. For example, when the reference source meta model is upgraded, the updated use destination data structure can be applied to an upgraded reference source meta model.SELECTED DRAWING: Figure 18

The invention discloses a software development project progress prediction management method based on artificial intelligence, and relates to the technical field of project management, and the method comprises the steps: extracting a causal relation from entity relation graph data, and constructing a causal knowledge graph; a graph structure analysis method and a time sequence prediction method are combined, predicted completion time and delay probability are calculated for the causal knowledge graph and the associated time sequence data, and a progress risk assessment result is generated; performing causal chain identification on the progress risk assessment result and the causal knowledge graph by adopting a causal reasoning method to generate delay interpretation information; according to the delay interpretation information, a preset resource priority and a task weight, a rule driving and priority scheduling strategy is adopted to construct a compensation scheduling scheme; and implementing a compensation scheduling scheme, collecting implementation effect data and analyzing a scheduling effect through a closed-loop feedback and dynamic adjustment mechanism, and generating an optimized scheduling management scheme. The intelligent level and the practical value of project progress management are greatly improved.

The invention provides an end-to-end intelligent system development method and system based on an AI large model. The method comprises the following steps: S1, receiving a system demand described by a user through a natural language; s2, analyzing the requirements through an AI large model and converting the requirements into formalized specifications; s3, automatically generating a system architecture and dividing components; s4, generating each component code in a recursive manner; s5, dynamically detecting and repairing the generated code problem; s6, automatically integrating all components to form a complete system; and S7, continuously optimizing the system based on system feedback or user feedback. According to the method, work of multiple stages such as demand analysis, architecture design, module division, code writing and testing is automatically completed, distributed integration and smart contract are performed, distributed integration verification is performed through a block chain smart contract and a graph database, data consistency, interface matching and security among components are ensured, the integration process is optimized, and the integration efficiency is improved. Cross-domain cooperation is achieved, and the development efficiency is high.

The invention relates to the technical field of software development, and provides a method and a system for generating a software development scheme. The method comprises the following steps: S1, acquiring a user demand, extracting a functional demand and a non-functional demand, and processing; s2, generating a system architecture design based on a demand analysis result, and selecting a proper technical scheme in a manner of combining a collaborative filtering model and reinforcement learning; s3, based on the architecture design and the demand analysis result, a development task is automatically generated, and resource scheduling is dynamically adjusted; and S4, generating an automatic test based on a demand, and performing intelligent analysis on a test result. And dynamically generating system architecture design and optimizing technical stack selection through a method of combining a collaborative filtering model and reinforcement learning. Collaborative filtering is associated with implicit vectors of a technology stack through user requirements, reinforcement learning optimizes decisions according to historical experience, expandability of architecture design and reasonability of technology type selection are guaranteed, different project requirements are met, and system performance is improved.

The invention provides a code peculiar smell detection method and system based on a large language model, and relates to the technical field of code peculiar smell detection.The method comprises the steps that context code information of a to-be-detected code is extracted, and the context code information comprises a method code and a class code; respectively extracting key information of the method codes and the class codes, and constructing a method information set and a class information set; constructing a large language model; on the basis of a thinking chain and a thinking tree, constructing cue words of the large language model; constructing a hierarchy-based code replacement strategy; dynamically adjusting the context code information by using the method information set and the class information set according to the code replacement strategy; and inputting the cue word and the dynamically adjusted context code information into the large language model for code odor detection, and outputting a code odor detection result of the to-be-detected code.

The invention discloses a design manuscript code generation and visual error iterative correction method and system based on multi-agent cooperation, and aims to solve the problems of low front-end code generation efficiency, poor visual restoration degree and lack of an automatic correction mechanism in the prior art. The system constructs a four-node state diagram based on LangGraph, automatically initializes a series engineering scaffold, obtains design data and generates a structured protocol, and generates a component code based on the protocol and performs visual verification and iterative correction on four processing nodes. The method comprises the following steps: dynamically generating an engineering scaffold through a large language model agent, converting Figma design data into a structured protocol, and carrying out iterative optimization by utilizing a judger-repairer mode until an error is lower than a threshold value; according to the method, high-fidelity automatic delivery from the design manuscript to the code is realized, and the executable front-end engineering code and the visual reduction degree analysis report are output.

An architecture includes multiple agents that communicate through structured dialectical exchanges to transform business requirements into executable applications. The agents are configured to collaborate and communicate through a series of iterative dialogues, where each agent contributes its specialized expertise to the process. The structured exchanges allow the agents to challenge, refine, and validate each other's outputs to automatically generate an application.

A method and apparatus for traceably managing software throughout its life cycle is disclosed. In one embodiment, the method comprises accepting, in secure management service via a first client interface module of a set of client interface modules, a request from a member of a plurality of members of the software supply chain to sign designated information, the designated information associated with the secure software in at least one of the plurality of stages, signing the designated information in response to the request according to a private key of a key pair uniquely associated with the member, and providing the signed designated information to the member of the software supply chain.

This invention discloses a full lifecycle management system and method for scientific computing programs. The system includes a build environment subsystem and a production environment subsystem. The former provides computer resources for the build process of the scientific computing program throughout its lifecycle, while the latter provides computer resources for the testing and deployment processes. This invention, through a full lifecycle management method for scientific computing programs, operates on corresponding computing resources, encompassing a series of steps including querying, triggering scheduling, build execution, result distribution, and test deployment. It automatically generates the executable file of the scientific computing program and configures its runtime dependencies. Simultaneously, it automatically generates a corresponding description file recording the entire lifecycle process. Furthermore, based on version management of these description files and their sets, it achieves full lifecycle traceability and cross-platform migration and deployment of scientific computing programs in a high-performance computing environment.

Code and text processing and analysis tools are provided for finding potentially sensitive information in a corpus of code. A request is received to analyze a corpus of code or text to find potentially sensitive information. Information unlikely to be sensitive is removed from the corpus of code or text to generate a modified copy of the corpus of code or text. Frequently occurring sections may also be removed as unlikely to be sensitive. An unpredictability score is determined for the remaining sections of the modified copy of the corpus of code or text, and the unpredictability score is used to prioritize unpredictable sections for review. Selectable section identifiers of the prioritized sections may be sorted in a code or text navigation interface and reviewed in a code or text viewing interface to determine whether the selected sections incorrectly contain sensitive information. If so, corrective actions may be triggered.

The embodiment of the invention discloses a software package management method and device, equipment and a storage medium, the method and device are applied to electronic equipment, the electronic equipment runs a sandbox, the sandbox comprises a software package manager and a target database, the target database is used for storing software package information of software installed in the sandbox, and the method comprises the steps that a processing request for a first software package is acquired; in response to the processing request, processing operation corresponding to the processing request is executed on the first software package through the software package manager and the target database, and the processing request comprises one of software package installation, software package updating, software package query or software package unloading. The lightweight software package manager can be used for managing the software package, so that the software package manager is convenient to use and maintain.

The invention discloses a burning management method and system for a burning upper computer. The method comprises the following steps: performing user identity verification according to user identity information of a burning applicant; after the user identity verification succeeds, performing burning permission verification on the to-be-burnt data; when the to-be-burnt data meets the burning authority, burning the to-be-burnt data, dividing the to-be-burnt data into a plurality of burning data frames, encrypting each burning data frame in sequence, and sending the encrypted burning data frames to the burning equipment; in the burning process, feedback data of the current burning data frame are received, burning verification is conducted on the current burning data frame according to the feedback data, and the burning baud rate of the next burning data frame is adjusted; after burning is completed, burning verification is carried out on the burning equipment, and the burning state of the to-be-burnt data is determined. Through the automatic and intelligent burning process, the burning efficiency and accuracy are improved. And the burning parameters are adjusted according to the burning condition, so that the burning stability and the burning speed in the burning process are ensured.

The present disclosure is directed to systems and methods that provide support for customized versions of functions that operate on a resource of a commerce platform by giving customers the ability to write custom versions of such functions that employ more advanced / complex logic that what is offered by default configurations for the functions. A custom scripting language may be added to the API of the commerce platform, which may allow customers to define scripts that specify the desired custom functionality. In response to receiving a request to customize the function from a customer, a function signature specifying information about the custom version of the function may be provided to the customer. Upon receiving a script defining a custom version of the function, the script may be stored on the resource object representing the resource the custom function is to operate on.

The invention relates to the technical field of plug-in resource management, and discloses an adaptive plug-in scheduling and dynamic optimization evolution method and system, and the method comprises the steps: obtaining a plug-in task generated by an edge calculation module based on a target device real-time monitoring index data flow; monitoring running state data of the plug-in system in real time and preprocessing the running state data; carrying out resource allocation on the plug-in task by utilizing a reinforcement learning algorithm based on the preprocessed data, and generating a plug-in task resource allocation result; performing plug-in resource allocation on the plug-in task and the plug-in task resource allocation result based on a virtualized resource pool mode to generate a plug-in resource allocation result; and generating a plug-in code based on a plug-in resource allocation result by utilizing a model-driven development and automatic code generation technology, and running a feedback result to optimize and evolve a plug-in. Through an intelligent and adaptive mechanism, the real-time response capability, the performance, the expandability and the sustainable development capability of the plug-in are remarkably improved.

The invention discloses a C + + Mock class automatic generation method based on an inverse memory agent and a contrast knowledge graph, and aims to solve the problems that a virtual function coverage gap in a large C / C + + code library is difficult to find, the Mock code maintenance cost is high, and the automatic repair efficiency is low. According to the method, a difference context matrix is constructed by analyzing and merging request patch metadata, and an incremental abstract syntax tree is generated; generating a backtracking queue based on the event intensity and the semantic overlapping degree, and extracting a virtual function change list; the multi-scale difference extraction is completed in combination with an external expansion operator according to the rule that the path is not disassembled and the node is movable; a self-adaptive strategy table and a Mock specification are generated, through code synthesis and lightweight compilation verification, automatic self-healing is achieved through root cause positioning and minimum cost repair, finally, a result is written into a knowledge graph, and parameters are dynamically adjusted. According to the invention, Mock generation accuracy and version adaptability are improved, manual intervention is reduced, and test maintenance efficiency is improved.

There is provided a system and method of automatic software testing. The method includes obtaining an input including software code of a software program and metadata, and feeding the input to a machine learning model to generate a test suite usable for testing the program. The test suite comprises a set of tests meeting a predefined condition. The test suite is generated by generating at least one question related to at least one of: expected intents of one or more sections of the software code, or tests for testing the sections, and presenting the at least one question to a user; upon receiving feedback from the user, analyzing the feedback with respect to the predefined condition, and determining whether to generate at least one new question; and, in response to an affirmative determination, repeating the above process with respect to the new question, until the predefined condition is met.

The invention relates to the technical field of model cross-scene application, and discloses a data model cross-scene management method and system.A judgment matrix is constructed through an analytic hierarchy process to quantify cross-scene demand importance, cross-scene demand priorities are sorted, a cross-scene flow chart is drawn, and a standardized data management system is constructed. A cross-scene data model is designed by adopting a layered architecture based on a standardized data management system, system docking and monitoring are realized through an AP I interface, service attribute characteristics and interface acquisition information of a scene are extracted, a scene data scale type and a real-time type are divided through a clustering algorithm, and a scene data real-time model is obtained; and distributing a basic computing power strategy for the scene according to the established computing power distribution strategy database, judging the data feature stability of the cross-scene data model in each scene by calculating a comprehensive drift index, and if the stability is low, triggering computing power distribution adjustment.

The invention discloses a software automatic operation and maintenance method and system based on an AI technology, and relates to the technical field of software automatic operation and maintenance. The method comprises the steps of establishing a software operation exception database; performing operation monitoring on the function modules, identifying the modules and parameters, generating a flow chart, verifying execution time and parameter use conditions, and processing according to results; risk parameters and function problems are extracted, partition is carried out through a decision tree, key parameters are determined through t-SNE and a clustering algorithm, and fault types are diagnosed according to an anomaly detection algorithm and an SVM model; monitoring risk parameters, calculating related indexes to obtain a comprehensive evaluation value and a risk index, and establishing and training a fault prediction model to evaluate the future performance of the software; and performing maintenance or optimization measures to prevent potential faults and realize automatic operation and maintenance of the software. According to the invention, the whole process management from data collection to automatic maintenance is realized, the accuracy and efficiency of fault diagnosis are improved, and the stability of the system and the capability of coping with a complex environment are enhanced.

The invention provides a software bill of material analysis method, which comprises the following steps: S1, selecting a software project to be evaluated, and ensuring that a code library of the software project is complete and accessible; s2, scanning the code library and the dependency relationship by adopting an analysis tool, and generating a software component report; s3, identifying a three-party service used in the software project according to the information obtained by scanning the code library and the dependency relationship; s4, according to all the content of the code library obtained through scanning and in combination with the recognized three-party service, self-research codes are accurately distinguished, and the code self-research rate is calculated; and S5, identifying key elements, structures, defects or security vulnerabilities of the codes, comparing the key elements, the structures, the defects or the security vulnerabilities with known correct results or expected results for analysis, and judging the quality of the self-research codes. According to the method, bill of material analysis can be comprehensively and accurately carried out on software projects, self-research codes are clearly defined, three-party services are effectively identified, and code quality is accurately evaluated.

The invention discloses a service integrated industrial software cloud base system, which belongs to the technical field of industrial software, and comprises an identity verification and authorization module, which is used for verifying and authorizing the identity of a user, and the authorized user can access an industrial software system; the data access management module is used for managing data access of the industrial software system and safely transmitting the data of the industrial software system; the data monitoring management module is used for managing industrial software system data monitoring and generating an industrial software system analysis report; and the remote maintenance management module is used for performing remote maintenance management on the industrial software system. According to the invention, the problem of poor use effect caused by incapability of accessing, monitoring and managing data of the industrial software system and incapability of maintaining and managing the industrial software system in the prior art is solved. According to the invention, effective access management and monitoring management can be carried out on the data of the industrial software system, the industrial software system can be maintained and managed in time, and the use effect can be improved.