Targeted Regression Testing via Component Mapping
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Solution Overview
Problem
Software testing systems face inefficiencies in resource allocation and test coverage, as they often require running full tests on all components, which can be time-consuming and resource-intensive, especially when only a subset of components has changed, leading to potential misses in bug detection and increased mean time to repair (MTTR).
Innovation Solution
A targeted regression testing system that selects a subset of test operations based on components that have changed, with a self-learning component that updates mappings between test scripts and software components using historical results, and performs shadow analysis to determine the risk and gains of targeted testing, allowing for intelligent resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full tests are run on all software components, then bug detection coverage is improved, but resource utilization and time consumption increase significantly
Solution Approach 1:
The patent segments the software code into multiple components and divides the test suite into targeted subsets corresponding to each component. Instead of running all tests on all components, the system executes only the relevant test subsets for each component, thereby reducing overall resource consumption while maintaining comprehensive bug detection coverage across the entire software system.
Solution Approach 2:
The patent applies partial action by running only a subset of tests on a subset of components rather than executing the full test suite on all components. The system determines which test subsets are necessary based on component changes or priorities, performing just enough testing to achieve adequate bug detection coverage without the excess resource consumption of complete test execution.
2Reliability
If full tests are run on all software components, then bug detection coverage is improved, but mean time to repair (MTTR) increases
Solution Approach 1:
By segmenting both the software components and test suites, the system enables parallel execution of multiple targeted test subsets. This segmentation allows bug detection to occur more quickly across different components simultaneously, reducing the overall time required to identify issues and thereby decreasing the mean time to repair.
Solution Approach 2:
The system performs preliminary analysis to identify which components have changed or are most critical before executing tests. By preparing and executing targeted test subsets in advance rather than running all tests, the system reduces the time required for bug detection and subsequent repair activities.
3Productivity
If targeted testing on changed components is implemented, then resource utilization is reduced, but bug detection coverage may be compromised
Solution Approach 1:
The patent implements dynamic test subset selection that adapts based on component changes, historical test results, and component criticality. The system dynamically determines which test subsets to execute for each component, adjusting the scope of testing based on current conditions. This dynamic approach ensures adequate bug detection coverage for changed components while optimizing resource utilization by avoiding unnecessary tests on stable components.
Solution Approach 2:
The system incorporates feedback mechanisms that use historical test results and component change information to refine test subset selection. By analyzing feedback from previous test executions and component modification data, the system continuously improves its ability to identify appropriate test subsets that maintain bug detection coverage while reducing resource consumption.
Data Source
AI summary
A software testing method. In particular implementations, a method includes accessing a first database of one or more bug entries, wherein each bug entry comprises information characterizing a bug, an associated code component, and a test script; and a mapping between the component and one or more scripts that test the code component; for one or more bug entries in the first database, determining if the bug is a new bug; if the bug is not a new bug, determining if the test script is new relative to the bug; and if the bug is a new bug or if the test script is new relative to the bug, accessing a second database of the script-to-component mappings to add a mapping between the test script and the associated code component of a respective bug entry.


