123 results about "Continuous integration" patented technology

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.

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.

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.

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.

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.

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 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.

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.

Systems and methods provide novel inventions for integrating mainframe applications into modern Continuous Integration / Continuous Deployment (CI / CD) pipelines using BEARDS (Build Engineering And Rapid Development System), a Java-based interface. BEARDS facilitates the automation of build, test, and deployment processes for mainframe applications by managing source code, dependencies, and artifacts in a technology-agnostic manner. The system dynamically generates Job Control Language (JCL) jobs to compile mainframe code, integrates with CI / CD tools like Jenkins, JFrog Artifactory, and Ansible, and ensures secure, compliant deployments through detailed instructions and verification processes. BEARDS also supports large artifact management, incremental builds, and seamless integration with cloud platforms, providing scalability and flexibility for complex applications. By bridging the gap between legacy mainframe systems and modern DevOps practices, the invention enables organizations to automate and streamline their mainframe development processes, reducing costs, improving efficiency, and maintaining the reliability and security of critical applications.

In one embodiment, a method includes generating an application programming interface (API) definition by observing traffic. The API definition is associated with an API definition name and an API specification. The method also includes mounting the API definition with an application and deploying the application by a Continuous Integration / Continuous Delivery (CI / CD) pipeline. The method further includes implementing a runtime API and mapping the runtime API to the API definition.

The invention relates to a software project continuous integration system, which comprises a parameter acquisition module used for acquiring user configuration parameters; the configuration determination module is used for determining target compiling configuration and target packaging configuration of the target project according to the user configuration parameters; the code acquisition module is used for acquiring a to-be-compiled source code of a target project; the compiling module is used for obtaining a target compiling file according to the target compiling configuration and the to-be-compiled source code; and the integration module is used for packaging the target compiled file according to the target packaging configuration to obtain a target packaged file. According to the application, the user configuration parameters are acquired through the parameter acquisition module, the target compiling configuration and the target packaging configuration of the target project are determined by the configuration determination module according to the user configuration parameters, and the to-be-compiled source code is compiled and packaged according to the target compiling configuration and the target packaging configuration by the compiling module and the integration module. Continuous automatic integration of software projects is realized, and the integration efficiency of the software projects is improved.

The invention provides a continuous integration test balance method and device based on dynamic quality evaluation and a medium, and belongs to the technical field of vehicles. The method includes monitoring a code submission event, capturing changes in the code submission event, forming change set data, and determining a quality assessment indicator from a plurality of data sources. And determining a comprehensive risk coefficient of current code integration by utilizing the set risk assessment model according to the quality assessment index and the change set data. And dynamically deciding a corresponding test execution strategy according to the comprehensive risk coefficient, driving a corresponding test suite according to the corresponding test execution strategy, and distributing a corresponding test task to obtain a test execution result. The efficiency of continuous integration testing is improved, and testing resources are optimized.

The application provides a continuous integration method, device, equipment, storage medium and program product, and relates to the technical field of computers, and the method comprises the following steps: calling a test tool to test GPU operator code based on a pre-trained AI test arrangement intelligent agent, and generating a code diagnosis report; generating code optimization suggestions based on the AI test arrangement intelligent agent and according to the code diagnosis report and GPU hardware information; and correcting the GPU operator code based on the code optimization suggestions to obtain target operator code. Through the above manner, artificial intelligence technology is introduced into the continuous integration process of the GPU operator code, automatic testing, automatic diagnosis analysis, automatic correction and automatic continuous integration of the GPU operator code are realized, which is beneficial to improving the efficiency of the continuous integration of the GPU operator code, optimizing the continuous integration effect, and ensuring that the target operator code obtained by correcting based on the code optimization suggestions can adapt to the hardware characteristics of the GPU.

The invention discloses an integration test method and device, electronic equipment and a storage medium, and relates to the technical field of tests.According to the integration test method and device, due to the fact that an authority operation menu can be dynamically matched according to a user function role, role operation redundancy is reduced; automatic scheduling of test plans is realized by calling an interface through an automatic test process engine, and manual intervention is reduced; and the failure log and the transaction global tracking identifier can be associated to generate a defect work order and push the defect work order, and test information circulation is broken through, so that the problems of low test efficiency, information splitting, difficult role collaboration and difficulty in meeting the requirements of agile development and continuous integration caused by multiple existing independent tools can be solved; the technical problems of influence on system testing comprehensiveness and response speed due to the fact that the system testing comprehensiveness and the response speed are solved, and the technical effects of improving the testing efficiency, eliminating information barriers, improving role cooperation, adaptation agility and continuous integration requirements and enhancing the system testing comprehensiveness and the response speed are achieved.

This invention provides a continuous integration testing system and method for application software, relating to the field of software testing technology. A control terminal constructs test tasks based on the code to be tested and a pre-configured test process, sends them to a test host, and the test host initiates the code to be tested and executes the test tasks through an integration testing module. The integration testing module integrates distributed testing units, which execute corresponding test tasks and output test results. The distributed testing units include page character testing units, page layout testing units, media performance testing units, navigation function testing units, refresh update testing units, and traffic / power testing units. A test result feedback module receives test results from the distributed testing units and feeds them back to the test host. This invention solves the problem that current testing systems can only test individual projects one by one, which is inconvenient for continuous integration testing and results in low testing efficiency, thus improving software testing efficiency.

A Service Level Objective (SLO)-based Continuous Integration / Continuous Development (CICD) framework is disclosed, which enables SLO-based Canary deployments, SLO-based chaos engineering, and / or SLO-based performance testing. The SLO-based CICD framework enhances and simplifies CICD pipelines and brings the pipelines in line with Site Reliability Engineering (SRE) best practices. By relying on SLOs rather than SLIs, the SLO-based CICD framework avoids the use of threshold-based alerts, which can be noisy and error prone, and the thresholds associated with threshold-based alerts can change over time due to changes in production volume. The SLO-based CICD framework uses multi-window burn rates when evaluating SLOs, which removes the reliance on a static, predefined thresholds of SLI threshold-based alerting, and removes sensitivity of such evaluations to changes in production volume.

The invention provides a continuous integration method, device and equipment, a storage medium and a program product, and relates to the technical field of computers.The method comprises the steps that based on a pre-trained AI test arrangement agent, a test tool is called to test GPU operator codes, and a code diagnosis report is generated; based on an AI test orchestration agent, generating a code optimization suggestion according to the code diagnosis report and GPU hardware information; and based on the code optimization suggestion, correcting the GPU operator code to obtain a target operator code. By means of the mode, the artificial intelligence technology is introduced into the continuous integration process of the GPU operator codes, automatic testing, automatic diagnostic analysis, automatic correction and automatic continuous integration of the GPU operator codes are achieved, the efficiency of continuous integration of the GPU operator codes is improved, the continuous integration effect is optimized, and the method is suitable for being popularized and applied. And it is ensured that the subsequent target operator code obtained through correction based on the code optimization suggestion can adapt to hardware characteristics of the GPU.

Example solutions protect a continuous integration / continuous deployment (CI / CD) pipeline. Examples collect data from a CI / CD pipeline execution data source and / or a CI / CD pipeline task data source. Based on the collected data, a feature group comprising a plurality of records is created. Each record in the feature group represents an execution of the CI / CD pipeline. An anomaly score is generated, using a model representing historical feature groups, for the feature group representing the execution of the CI / CD pipeline. If the anomaly score is above a threshold, an alert is generated to indicate that the collected data represents an anomalous activity.

The invention discloses an assembly line construction method and system for version automatic marking, and the method comprises the steps: completing information collection and writing by an automatic deployment tool according to a self-defined metadata structure, monitoring code submission through Webhook, and transmitting a trigger signal; the continuous integration server pulls the latest submitted code from the code warehouse and executes construction operation; after the construction is passed, constructing an application mirror image, and pushing the application mirror image to a specified mirror image warehouse; and the automatic deployment tool pulls the application mirror image of the corresponding version from the mirror image warehouse, and starts the application in the target environment to complete the automatic deployment of the project. According to the method, the correlation tracing efficiency of the code version information and the construction product is improved, the manual recording and maintenance cost is reduced, and the reliability and maintainability of automatic deployment are improved.

The invention discloses a module use condition statistical method and device, equipment and a storage medium. The scheme is performed by an automated script deployed in a persistent integration environment. According to the method, function module type information in modeling project files is extracted in batches, the use relation between each project file and a function module type is established based on a predefined function module type list, and a structured statistical report is generated. According to the scheme, a traditional manual statistical mode is replaced by an automatic process, batch processing of multiple project files is realized, and the statistical efficiency is remarkably improved. Standardized information extraction and relation construction logic are adopted, so that the accuracy and consistency of statistical results are ensured. The generated standardized report provides reliable module use data support for engineering management, and the scientificity of module reuse analysis and resource optimization decision is effectively improved.

The invention provides a big data cluster deployment method and device, electronic equipment and a storage medium, and realizes full-process automatic deployment of a big data cluster through a containerized continuous delivery platform and a parameterized assembly line. According to the scheme, mirror image construction, component compiling and cluster installation are automatically executed, the deployment period is shortened from several days to several hours, human errors are avoided while efficiency is remarkably improved, and deployment accuracy is guaranteed. Through the unified product warehouse and standardized construction parameters, the consistency of the basic mirror image and the component version in different environments is ensured, the component compatibility problem is fundamentally solved, and the cluster stability and the cross-platform deployment capability are enhanced. According to the finally constructed complete continuous integration and delivery system, rapid and repeatable automatic deployment is realized, and the operation and maintenance agility and the system reliability are greatly improved.

Examples include a system that receives job configuration information for execution of a process including a plurality of stages, each stage including a plurality of sequences, each sequence including a plurality of pipelines, each pipeline including a plurality of operations to be executed sequentially. The plurality of sequences of a first stage are executed in parallel, with each sequence corresponding to a respective resource group, each respective resource group including a copy of resources from a base resource group specified by the job configuration information. Following completion of execution of the plurality of sequences of the first stage, the plurality of sequences of a next stage are executed, such that the plurality of stages are executed one at a time in a specified order until execution of the plurality of stages is completed. Following completion of execution of the stages, results of the process are sent to a computing device.

The invention discloses an intelligent attribution method for a continuous integration assembly line abortion problem, and the method comprises the steps: collecting a key abortion log, a code change context, an assembly line configuration context and a domain knowledge template through a multi-dimensional data mining pipeline in a structured manner; a two-stage retrieval mechanism is combined with a position-sensitive reverse ranking fusion algorithm to accurately match historical related cases from a hierarchical abortion case knowledge base, and a retrieval enhancement generation technology is utilized to drive a large language model to perform thinking chain reasoning. And dynamically optimizing the attribution result through a confidence evaluation strategy, and reversely updating the audited case features to the knowledge base to form a self-supervision expansion capability. According to the method, fine-grained accurate classification of six types of typical assembly line abortion problems can be realized, a user can be helped to quickly and accurately judge problem types and abortion reasons and provide effective detailed description support, the workload of abortion problem investigation is greatly reduced, and the robustness of a continuous integrated assembly line is effectively guaranteed.

The invention belongs to the related technical field of intelligent cabin acceptance, and provides an intelligent cabin acceptance method and system based on a continuous integration and continuous delivery technology, which systematically introduces the continuous integration and continuous delivery technology into an intelligent cabin system acceptance process to realize an integrated closed loop of development, construction, test, acceptance and deployment. According to the method, the whole process of the intelligent cabin software from code submission to real vehicle deployment does not need a large amount of manual intervention, a standardized CICD acceptance system adaptive to the vehicle-mounted system is formed, the problems that in the prior art, feedback of the acceptance process is lagged, and the online period is long are solved, and the high-frequency and agile iterative development requirements of the intelligent cabin software can be better met.

Aspects of the subject disclosure may include, for example, obtaining a model file and a context file associated with an environment-as-code (EaC) service, committing the model file and the context file utilizing a source control software service, and in response to the committing, building a set of instructions as part of a pipeline associated with the EaC service for utilizing a continuous integration and continuous deployment (CI / CD) software application. Further embodiments may include assembling infrastructure-as-code (IaC) software from a curated library of software patterns based on the model file and the EaC service, configuring a group of workspaces for a IaC provider software application based on the set of instructions as part of the pipeline, and providing provisioning instructions to a cloud provider server to provision computing resources based on the group of workspaces. Other embodiments are disclosed.

Methods, system, and non-transitory processor-readable storage medium for regex engine system are provided herein. An example method includes a Continuous Integration / Continuous Delivery (CI / CD) pipeline that triggers a regex engine system to scan source code. The regex engine system scans the source code for a plurality of regular expressions, and determines a regular expression vulnerability assessment associated with the plurality of regular expressions. The regex engine system generates a regular expression vulnerability assessment report comprising the regular expression vulnerability assessment.

A system that captures runtime data for a pipeline execution, generates an intermediate hierarchical file that includes relationships between the captured data, and converts the intermediate file to alternative format pipeline files, such as YAML files. The present system employs dynamic instrumentation of pipeline executions, regardless of their type, to capture data during pipeline execution. This approach not only facilitates the capture of comprehensive execution data but also leverages this information to seamlessly generate equivalent pipelines on alternative continuous integration platforms.