208 results about "Continuous integration" patented technology

The invention discloses a code fingerprint-based open source component identification and vulnerability detection method, which comprises the following steps of: receiving a local or remote code, extracting a difference file, generating an AST and constructing a code attribute graph; sHA-256 Hash fingerprints and GNN semantic fingerprints are calculated for the function level sub-graphs to form mixed fingerprints, accurate matching is conducted through a Bloom filter, semantic matching is completed through nearest neighbor, and a component version is determined through a distribution difference algorithm. The method comprises the steps that firstly, a component identifier is mapped into a PURL or an SWID, an OSV / NVD library is inquired to obtain a CVE, comprehensive risks are calculated in combination with CVSS, EPSS and dependency depth, and an SBOM and a vulnerability report conforming to CycloneDX or SPDX are output. The method is high in speed and high in accuracy, and the open source risk can be automatically treated in continuous integration.

Techniques are provided for software deployment pipeline generation using generative artificial intelligence (AI). One method comprises obtaining a trained generative AI model, trained using a plurality of continuous integration / continuous deployment (CI / CD) configuration files; obtaining information characterizing a selected software development project; and applying at least some of the information characterizing the selected software development project as one or more system prompts to the trained generative AI model, wherein the trained generative AI model predicts a portion of a software deployment pipeline associated with the selected software development project. The CI / CD configuration files used for training may be associated with an organization that is associated with the selected software development project. The predicted portion of the software deployment pipeline may comprise pipeline jobs, an automatic code completion and / or a correction of a syntax and / or a structure of at least one CI / CD configuration file being edited.

The invention discloses a research and development test bidirectional synchronization method based on artificial intelligence, and particularly relates to the technical field of artificial intelligence and software testing. Deep semantic modeling of research and development task behaviors is realized by constructing a multi-modal causal intention map, a test coverage blind area is inferred and recognized based on a graph neural network, a completion task is reversely generated, a complete state set is formed in combination with an original task set, and a condition control vector is adopted to drive generation of a structured test case. Collecting behavior and operation logs after the test is executed, detecting a mismatch area through modal alignment, generating a repair suggestion by utilizing a deviation correction model, and automatically writing back a task system; meanwhile, a state graph dynamic updating mechanism and a reverse task scheduling engine are introduced, and linkage feedback of test results on research and development tasks is achieved; the method can improve test coverage precision and research and development cooperation efficiency, and is suitable for agile development and continuous integration scenes.

The invention relates to the technical field of software engineering, and discloses an assembly line flow adaptive configuration method and system. The method comprises the following steps: obtaining source code data of a software project and performing static analysis and feature extraction to generate structured language description data; querying and matching in a preset template library based on the structured language description data to generate a task template set; performing task dependency relationship analysis and process topology assembly on the task template set to generate initial pipeline data; and performing dynamic strategy adjustment on the execution process of the initial pipeline data by adopting the real-time context data corresponding to the software project to generate target pipeline data. Through automatic language recognition and intelligent process generation, automatic configuration of the continuous integration process is realized, and the technical problem of low automation level caused by lack of automatic recognition and adaptation capability for a project development language environment in a project continuous integration and continuous deployment technology is solved.

The invention relates to the technical field of mobile application continuous integration automation, and discloses a multi-channel APP automatic packaging system which comprises the steps that byte code files in a released mobile terminal APP installation package are acquired, and an occupied symbol space set is generated; generating an available confusion namespace by using set complementary operation; extracting method-level code change by using an abstract syntax tree difference algorithm, and generating a change method set; generating a patch special confusion rule for the change method set by using a namespace allocation algorithm; compiling and obfuscating the change method set by applying a patch special obfuscating rule to generate a safe obfuscating patch byte code; performing packaging and signature operation on the safe obfuscation patch byte code, and outputting a minimized obfuscation safe hot repair patch pack; according to the method, the technical problems that class definition conflicts or method calling errors occur after the hot repair patch is loaded, and the downloading success rate of a user is affected due to the overlarge size of the hot repair patch are solved.

The invention belongs to the technical field of automatic testing, and particularly relates to a web automatic testing method and system.The method comprises the steps of automatic script recording and dynamic adaptation, layered framework collaborative testing and data verification and continuous integration testing and test report generation. Wherein automatic script recording is dynamically adapted: recording a page operation script through a playwright tool and applying the page operation script to a UI layer, and when the page UI changes, recording the script again and replacing the original script without element-by-element positioning and code modification; in the hierarchical framework collaborative testing and data verification, a data access layer inputs test data, a UI layer executes page operation and captures display data, and a business logic layer calls an API interface to obtain real data and compares the real data with the display data for verification. According to the method, a web automatic test framework is constructed in combination with the advantages of playwright, a structured engineering project is more suitable for project operation and maintenance, and a sustainable integrated test environment is constructed by utilizing jenkins, so that test input, execution and output are automated.

The invention discloses an automatic testing method and device based on a front-end UI and a terminal, and belongs to the technical field of front-end development testing. Comprising the following steps: detecting a first test instruction of each set of front-end UI program, controlling to carry out demand analysis, determining a function module which needs to be subjected to UI automatic test according to a demand analysis result, and determining a test target; performing automatic technology type selection, and selecting a specified test tool and a continuous integration tool; generating a compiled test case according to the determined function module needing to be tested and the test target; running the test case, and generating a test script according to the test case and an automation technology type selection result; when the test script is verified to be correct, integrating the test script into a continuous integration tool, and automatically running a test through the test script when the code of the subsequent version of the front-end UI program is submitted; and generating a test report, positioning problems and giving repair suggestions. According to the invention, the testing efficiency is improved, and the labor cost of testing is reduced.

A data processing system implements after determining that a test in a target branch of a code repository starts failing, receiving a pull request (PR) onto the target branch and blocking the PR (invoking a build policy and a test policy); after determining that the failing test in the target branch is disabled, tracking the disabled test in a disabled test file; in response to a request to requeue the test policy, determining whether artifact in the build policy is identical with artifact in the test policy; when not identical, fetching all versions of the file within a time period, generating a union content of all versions of the file, and applying the requeued test policy using the union content, the time period being between a start time of the build policy and a start time of the requeued test policy; and unblocking the PR.

Systems, devices, and methods related to automated management of deployment of applications are provided. An example computer system includes one or more processors and a computer-readable storage media storing computer-executable instructions. The instructions when executed by the one or more processors, cause the computer system to receive a request for deploying an application in a production environment, access data generated during continued integration / continued development (CI / CD) pipeline execution of the application, analyze the data to determine a status of the application, determine whether the application is ready for deployment based at least in part on the status of the application and a predetermined policy, and block the application from deployment in response to a determination that the application is not ready.

A method in one embodiment comprises implementing a first process for carrying out an application deployment configuration change using a deployment repository, and implementing a second process for carrying out an application logic change using a source repository, the second process being different than the first process. The method further comprises identifying a particular type of change to be made to at least one application, and controlling execution of a particular sequence of one or more instances of at least one of the first process and the second process responsive to identification of the particular type of change to be made to the at least one application. The deployment repository and the source repository are illustratively part of a continuous integration / continuous deployment (CI / CD) system. The CI / CD system controls software code for applications executed by host devices of a host platform coupled to the CI / CD system over at least one network.

The invention relates to the technical field of ship manufacturing, and discloses a general assembly construction data service encapsulation and construction method based on a cloud native technology. The method comprises the following steps: dividing a ship final assembly construction data source into design, production, quality inspection, logistics and operation and maintenance data units, and determining a data type and an interface protocol; then, constructing an initial service model based on a micro-service architecture and a containerization technology; then, dynamic service packaging is carried out, and cross-model data routing and load balancing are achieved; dynamically allocating resources and scheduling tasks through a multi-target scheduling algorithm model; iteratively optimizing the service model by utilizing an incremental learning mechanism; and finally, realizing gray release and rolling update by continuously integrating and continuously delivering assembly line deployment to a cloud native platform. The ship general assembly construction data processing efficiency, the system performance and the service quality are improved, and the problems of disordered data management, low processing efficiency, unreasonable resource allocation and the like in a traditional mode are effectively solved.

An agent deployment request is received for an external computing environment. An agentic module is configured for deployment to the external computing environment based on characteristics of the external computing environment, wherein the agentic module comprises a computational agent operable to process information stored within the external computing environment and a corresponding agentic controller. Responsive to the agent deployment request, a first unit of software instructions is generated that, when executed, instantiates an agentic module instance within the external computing environment. The first unit of software instructions is transmitted to the external computing environment. A performance metric related to processing of the information stored within the external computing environment by a computational agent instance of the agentic module instance is received from an agentic controller instance of the agentic module instance.

The invention discloses an increment testing method and device, a storage medium and electronic equipment, and the method comprises the steps: constructing a dependency graph for describing the dependency relationship between software components in a software system according to software system data, and carrying out the continuous integration of the software components on the basis of a code change set corresponding to a current continuous integration task; a minimum candidate influence range is determined on the dependency graph, a candidate test set is delineated, tests in the candidate test set are ranked according to the sequence of risk scores of all the tests from high to low, a target candidate test set is obtained, all the tests are processed through a greedy approximation algorithm, and a target candidate test set is selected under the constraint of resource budget; and the minimum and optimal test set of software system defects is found to the maximum extent. According to the method, the minimum candidate influence range is determined on the dependency graph based on the code change set, the greedy approximation algorithm is combined, intelligent and accurate selection of the test set under the resource budget constraint is achieved, it can be guaranteed that the defect detection rate is not reduced, and the continuous integration process efficiency can be improved to the maximum extent.

A method includes identifying a pipeline of a plurality of pipelines of a continuous integration and continuous delivery / deployment (CI / CD) system, selecting a repository of a plurality of repositories utilized by the identified pipeline, modifying the repository, determining whether to test the modified repository and responsive to determining to test the modified repository, executing the identified pipeline with the modified repository.

Various methods and processes, apparatuses or systems, and media for automating development, testing, and productionizing a pipeline for users are disclosed. A processor receives a request from a user to access an application, the request including user's credentials data; grants access to the application based on verifying the user's credentials data with prestored credentials data received by calling an authentication server; identifies the user's role within a computing environment; automatically presents a template that corresponds to the user's role allowing the user to write code to source data either by bringing the user's own data into the computing environment or by connecting to data that resides in a database; automatically integrates the written code with a continuous integration continuous delivery pipeline for production of a model; and deploys the model after training and testing the model while managing and maintaining all necessary guardrails from a control standpoint within the computing environment.

Embodiments disclose a honeyrepo implemented in a cybersecurity computing environment. A honey repository is configured for inclusion in a source control system by a detection and response server that is communicatively coupled to a continuous integration system that accesses a shared repository and has access to individual repositories of the source control system by generating a honey repository configuration package that includes decoy metadata to entice an attacker to initiate a request to access the honey repository. The honey repository configuration package that includes the decoy metadata is transmitted to the source control system to generate the honey repository and access to the source control system is monitored at the detection and response server. If an attacker initiates the request to access the honey repository, access is disabled for the attacker to the individual repositories of the source control system and the shared repository managed by the continuous integration system.

One embodiment of the present invention relates to a computer-automated system and method for identifying copyrighted source code embedded within other source code files, utilizing advanced semantic analysis techniques. This embodiment of the invention addresses the challenge of detecting both literal and non-literal copies of copyrighted code, including instances where the code has been modified in non-semantic ways, such as through renaming variables, changing formatting, or rearranging code blocks. This embodiment creates semantic embeddings of source code using a large language model (LLM). Each segment of source code is transformed into a high-dimensional vector that captures its semantic essence, rather than its literal text. These vectors are then compared using sophisticated similarity metrics, such as cosine similarity or L2 distance, to determine the likelihood of copyright infringement. This embodiment can operate without direct access to the full source code, thereby enhancing privacy and security. Instead, the system works with embeddings that represent the semantic information of the code, significantly reducing the risk of data exposure. Additionally, this embodiment of the invention includes an optional compression module that further minimizes the data footprint by compressing the semantic vectors, enhancing the system's efficiency and scalability. This embodiment of the invention is particularly suited for use in environments where large volumes of code need to be analyzed quickly and accurately, such as in continuous integration / continuous deployment (CI / CD) pipelines. It provides a robust, scalable, and secure solution for managing copyright compliance in software development, offering significant improvements over traditional text-based or hash-based comparison methods.

The invention relates to the technical field of embedded system software development and continuous integration, in particular to a docker-based AGV (automatic guided vehicle) cross compiling method, which comprises the following steps of: constructing an ARM (advanced RISC machines) root file system on an x86 development host by using a virtualization tool, configuring a header file and a dependency library, and packaging and compressing to obtain an ARM root file system mirror image; pulling the basic mirror image from the public warehouse to create an x86 Docker container, copying the ARM mirror image to a specific path of the container and mounting the ARM mirror image to prepare a Docker mirror image special for AGV cross compiling; writing a CMake cross tool chain file in the container, introducing an ARM mounting path, setting a dependency path and appointing a tool chain; then integrating the commands, automatically updating the container through mirror image ID comparison, and constructing operation commands such as Makefile packaging and compiling and the like at the same time; and finally, calling an integration command to start cross compiling, and generating a program capable of running on an ARM board card of the AGV. According to the method, unified and efficient multiplexing of the AGV cross compiling environment can be realized, the development efficiency is improved, the maintenance cost is reduced, and the method is adaptive to an AGV project needing cross compiling.

A method in an illustrative embodiment comprises configuring a software development process to include at least first and second software-based agents for interacting with one another and with at least one large language model (LLM). The method further comprises assigning a first role in the software development process to the first software-based agent, assigning a second role in the software development process to the second software-based agent, initiating interactions between the first and second software-based agents and between each of the first and second software-based agents and the at least one LLM, determining estimates for completion of respective work items of the software development process based at least in part on the interactions, and adjusting one or more characteristics of the software development process based at least in part on the estimates. The software development process is illustratively part of a continuous integration / continuous deployment (CI / CD) system.

The invention provides an interface change risk management and control method and device based on multi-source evidence fusion, and the method comprises the steps: carrying out the standardization processing of interface call data from various heterogeneous evidence sources, and generating a unified endpoint set and a call relation set; fusing the multi-source data pointing to the same calling relationship to calculate the confidence of the multi-source data, and constructing a service dependency topological graph based on a high-confidence relationship; when an interface change is detected, analyzing an influence range of the change in the topological graph, quantitatively calculating an influence surface score, and dynamically judging a risk level; and implementing corresponding automatic management and control actions in the continuous integration / continuous delivery process according to the risk levels. According to the method and the device, the problem of frequent interface change online faults caused by inaccurate dependence identification, inaccurate change influence evaluation and risk management and control lagging can be solved, the risk discovery and management and control of interface definition destructive change can be advanced from online to before-online, and the online fault rate is further remarkably reduced.

The invention discloses a code item management method and device, and relates to the technical field of operation and maintenance management. The method comprises the steps of executing a configuration management operation on a code warehouse corresponding to a code item; the configuration management operation is used for managing attribute information of code items in the code repository; setting assembly line parameters of the assembly line operation process, wherein the assembly line parameters are trigger factors for triggering the assembly line operation process; an operation instruction is received, a corresponding assembly line execution task is constructed when an assembly line operation process is triggered based on the operation instruction, and the operation instruction comprises assembly line parameters; obtaining a corresponding code item based on the assembly line execution task, performing operation, and displaying an execution state and an execution result through a preset continuous integration tool; and according to the execution state and the execution result, triggering a code item configuration process to carry out warehousing storage on the adjusted code item. The method and the device are used for realizing a code project management function.

A common data model is created for an automation system, which includes an ontology of semantic relationships between entities of the automation system captured from multiple simulation tools based on a simulation design of the automation system. Artifacts, such as simulation and automation artifacts may be attached to corresponding entities in the common data model. New automation artifacts may be generated utilizing logic definitions from the simulation artifacts in the common data model. Changes to an artifact may be propagated to affected artifacts in the common data model utilizing dependencies defined by the semantic relationships. A snapshot of the common data model, including the newly generated or modified artifacts are committed to a version control system. A continuous integration execution engine executes virtual commissioning for validating each automation artifact against a simulation environment in a simulation of the automation system, based on the commit of the common data model.

The present application provides a testing method and a testing system, which can perform a power-on test on a newly submitted first code through a first electronic device before merging the code into a main branch of the code after continuous integration verification in a typical software development process, or perform a power-on test on a newly submitted first code through a first electronic device during continuous integration verification in a typical software development process, or perform a power-on test on a newly submitted first code through a first electronic device before continuous integration verification in a typical software development process. The typical software development process includes continuous integration verification, merging the code into a main branch of the code, etc. Since the present application performs a power-on test on the code before merging the code into the main branch, the efficiency of locating "problem code" can be improved, so that the "problem code" can be located in a shorter time, thereby improving the overall R&D efficiency.

The invention discloses a software integration method and device, equipment, a storage medium and a program product, and belongs to the technical field of software. The software integration method comprises the steps that a first configuration file and a second configuration file are generated, the first configuration file and the second configuration file comprise various kinds of configuration information needed by M software modules in a currently constructed software package, and M is an integer larger than 1; generating M sub-assembly line tasks according to the first configuration file, wherein the M sub-assembly line tasks are used for constructing the M software modules in a one-to-one correspondence manner; and according to the second configuration file and the trigger assembly line corresponding to the M software modules, coordinating the calling sequence of the M sub assembly line tasks, running the M sub assembly line tasks through the assembly line, and running the M sub assembly line tasks through the assembly line to complete construction of the M software modules. According to the invention, the technical problem that the iteration speed of the intelligent driving system is seriously restricted by the existing continuous integration technology is solved.

The invention provides a large-scale complex software system test case recommendation method based on deep reinforcement learning, which forms deep cognition of a model on a case by providing analyzable case-code-defect multi-layer features, and constructs dynamic features for describing selected cases at the same time, so as to recommend the test cases of the large-scale complex software system. The complementarity and redundancy among the cases are comprehensively considered by the model, and the group-level test case recommendation ability is improved. In addition, through a multi-cycle adaptive training reinforcement learning structure, the method has high adaptability to a dynamic environment, and automatic use case recommendation can be achieved according to code fireworks. The improvement of the capabilities realizes more intelligent and more efficient test case recommendation, and is helpful for improving the defect detection efficiency and the test resource utilization rate of software testing in a continuous integration environment.

The application discloses a test case data processing method, device, equipment, storage medium and program product. The method comprises the following steps: acquiring a full-amount test case set, generating an ordered test case list based on the full-amount test case set; traversing the ordered test case list in a forward order, and determining a test case traversed in the traversal process as a target test case; executing the target test case, and judging the target test case as a valid test case or a redundant test case based on an execution result. The method can reduce the number of test case sets corresponding to code files, avoid unnecessary test execution, reduce the test running scale, reduce the time cost and the calculation resource consumption caused by redundant test running, and finally improve the continuous integration and delivery efficiency in the software development process.

A method of improving continuous integration, continuous delivery (CI / CD) pipelines includes receiving an indication of a failure of a CI / CD pipeline of a plurality of CI / CD pipelines. The method further includes processing build status information by a rule engine, the build status information indicative of builds executed within the plurality of CI / CD pipelines. The method further includes applying a set of rule to the build status information to select a subset of the plurality of CI / CD pipelines, wherein the set of rules includes one or more of a resource availability rule or a failure type rule. The method further includes executing the subset of CI / CD pipelines selected by the rule engine.

A code commit facility is provided operatively coupled to a continuous integration continuous deployment system to assist in addressing a failing code change during updating of a software application. The code commit facility includes generating discrete code change packages from the failing code change by separating independent code change files of the failing code change into the discrete code change packages. Further, the code commit facility deploys the discrete code change packages and based on the deploying, detects a failing discrete code change package. Based on detecting the failing discrete code change package, the code commit facility rolls back one or more code change files of the failing package, absent rolling back one or more other code change files of one or more other discrete code change packages to restructure the failing code change for deployment using the continuous integration continuous deployment system.

The application relates to the field of software testing, and provides an automatic testing and closed-loop repair method, device and storage medium for wireless device software. The method comprises the following steps: listening to a communication channel during wireless device operation, acquiring air interface data containing at least a Bluetooth or Wi-Fi protocol and corresponding radio frequency environment metadata; performing multidimensional analysis on the air interface data by using a machine learning model; automatically generating a machine executable defect report according to a predefined structured template based on the result of the multidimensional analysis; parsing an automatic repair trigger instruction in the machine executable defect report, automatically calling an application program interface of an external continuous integration system to trigger a code pulling, compiling and testing task chain for the defect; after the task chain is successfully completed, wirelessly pushing an update program generated to the wireless device, and when the pushing fails or the device runs abnormally after being updated, performing a predefined automatic retry operation or a predefined version rollback operation.