Abstract: A pipeline management system that allows for creating and managing pipelines and pipeline execution. The system allows a user to create pipeline stages, steps for the pipeline stages, and commands for the pipeline steps. The system efficiently allows users to create and manage multiple pipelines by allowing attributes of commands, such as for example variables in the commands, to be entered at runtime. The runtime entry attributes for a pipeline make up an input set. A pipeline can be bound with one or more input sets that are used to fill or instantiate the pipeline variables at runtime.

Abstract: A system that automatically reduces test cycle time to save resources and developer time. The present system selects a subset of tests from a full test plan that should be selected for a particular test cycle, rather than running the entire test plan. The subset of tests is intelligently selected using metrics such as tests associated with changed code and new and modified tests.

Abstract: A system that automatically reduces test cycle time to save resources and developer time. The present system selects a subset of tests from a full test plan that should be selected for a particular test cycle, rather than running the entire test plan. The subset of tests is intelligently selected using metrics such as tests associated with changed code and new and modified tests.

Abstract: A release combination including a plurality of software artifacts is generated. A first plurality of tasks on a validation server can be associated with a validation operation of the release combination. A second plurality of tasks on a production server can be associated with a production operation of the release combination. First data from execution of the first plurality of tasks with respect to the first release combination may be automatically collected. An automated execution of the first plurality of tasks on the validation server may be shifted to the second plurality of tasks on the production server responsive to a quality score of the release combination that is based on the first data.

Abstract: A computer system is configured to provide automated deployment and testing of a first build combination based on identification of a software artifact, among the set of software artifacts of the first build combination, as including a modification relative to a second build combination. Among test assets stored in a database, a subset of the test assets is associated with a test environment for the first build combination based on the software artifact comprising the modification and a risk score associated therewith. A server in the test environment is automatically provisioned based on the subset of the test assets associated with the test environment, and the first build combination is deployed to the test environment responsive to the automated provisioning of the server.

Abstract: A computer system is configured to provide automated deployment and testing of a first build combination based on retrieving, from a data store, code coverage data indicating respective software artifacts that were tested by execution of a plurality of test cases. The test cases are associated with the respective software artifacts that were tested by the execution of the test cases based on corresponding temporal data. Automated testing is executed for a build combination including one of the respective software artifacts, where the automated testing includes a subset of the test cases. The subset includes ones of the test cases associated with the one of the respective software artifacts based on the corresponding temporal data.

Abstract: A computer system is configured to provide automated testing of a second build combination based on retrieving, from a data store, test result data indicating execution of a plurality of test cases for a first build combination that includes a software artifact that has been modified relative to a previous build combination. A subset of the test cases is associated with the software artifact based on the test result data, where the subset includes test cases that failed the execution of the test cases for the first build combination. Automated testing is executed for a second build combination including the software artifact, where the automated testing includes the subset of the test cases. The second build combination may be subsequent and non-consecutive to the first build combination.

Abstract: First data related to first validation operations for a plurality of first release combinations is stored, where the first validation operations comprise a first plurality of tasks. Production results for each of the plurality of first release combinations are stored. Second data from execution of a second plurality of tasks of a second validation operation of a second release combination is automatically collected. A quality score for the second release combination based on a comparison of the first data, the second data, and the production results is generated. Responsive to the quality score, the second release combination is shifted from the second validation operation to a production operation.

Abstract: A set of artifacts is identified for deployment on a target device in a deployment. The set of artifacts are from a source computing system remote from the target device. A cache device can be determined as corresponding to the target device, the cache device separate from the target device. The set of artifacts are pre-distributed on the cache device in advance of the deployment. The set of artifacts are sent to the cache device from the source computing system to be held at the cache device prior to the artifacts being distributed to the target device. The deployment follows distribution of the set of artifacts on the target device.

Abstract: Particular deployment logic is selected that describes a plurality of steps in a type of software deployment. Release data is identified that defines a selection of a set of software artifacts to be deployed in a particular deployment. Further, environmental data is selected that describes configuration of a target system for the particular deployment. First associations are determined, using data processing apparatus, between steps in the plurality of steps and software artifacts in the set of software artifacts. Second associations are determined between steps in the plurality of steps and configuration information of the target system used in the respective steps. The artifacts are automatically deployed on the target system, using one or more data processing apparatus, based on the first and second associations.

Abstract: Particular deployment logic is selected that describes a plurality of steps in a type of software deployment. Release data is identified that defines a selection of a set of software artifacts to be deployed in a particular deployment. Further, environmental data is selected that describes configuration of a target system for the particular deployment. First associations are determined, using data processing apparatus, between steps in the plurality of steps and software artifacts in the set of software artifacts. Second associations are determined between steps in the plurality of steps and configuration information of the target system used in the respective steps. The artifacts are automatically deployed on the target system, using one or more data processing apparatus, based on the first and second associations.

Abstract: A set of artifacts is identified for deployment on a target device in a deployment. The set of artifacts are from a source computing system remote from the target device. A cache device can be determined as corresponding to the target device, the cache device separate from the target device. The set of artifacts are pre-distributed on the cache device in advance of the deployment. The set of artifacts are sent to the cache device from the source computing system to be held at the cache device prior to the artifacts being distributed to the target device. The deployment follows distribution of the set of artifacts on the target device.