Survived Mutation Blaming with Test Case Localization
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Solution Overview
Problem
Conventional mutation test tools struggle with high false positive rates, require different plugins for different build systems, have limited test failure tolerance, and provide limited stability, making it difficult to accurately identify and upgrade test suites to kill surviving mutations.
Innovation Solution
A system and method that automatically apply specified test case identification rules to a list of tests covering a surviving mutation, filtering and matching names to identify the responsible test case or class, allowing developers to modify or write new tests to kill the mutation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional mutation test tools are used to identify survived mutations, then mutation testing can be performed, but the tools provide only block coverage reports making it very difficult to understand which specific part of the test suite failed
Solution Approach 1:
The patent segments the test suite analysis by identifying and reporting the specific test case or test class responsible for each survived mutation. Instead of providing only aggregate block coverage reports, the system breaks down the information to show exactly which test case failed to kill the mutation, enabling precise localization of test deficiencies.
2Reliability
If conventional mutation test tools are used, then mutation testing can be performed, but they have significant rates of false positive reporting (e.g., 20-50%)
Solution Approach 1:
The patent implements feedback mechanisms where the system not only identifies survived mutations but also provides actionable information about which specific test cases failed to detect them. This feedback loop enables developers to understand why false positives occurred and make targeted improvements to the test suite, thereby reducing future false positive rates and improving overall reliability.
3Adaptability or versatility
If conventional mutation test tools are used, then mutation testing can be performed, but they require different plugins for different build systems (e.g., pitest maven plugin, pitest ant plugin, etc.)
Solution Approach 1:
The patent creates a universal mutation testing system that can operate across different build systems without requiring separate plugins. The system is designed to be build-system-agnostic, providing a single unified interface that works with various build tools, thereby eliminating the complexity of configuring and maintaining multiple plugins while maintaining broad adaptability.
4Reliability
If conventional mutation test tools are used, then mutation testing can be performed, but they have limited test failure tolerance and limited stability (e.g., buggy)
Solution Approach 1:
The patent implements robust error handling and stability mechanisms that cushion against test failures and tool bugs. The system is designed to gracefully handle edge cases, configuration issues, and unexpected failures without crashing or producing incorrect results, thereby maintaining high reliability and stability even in challenging testing scenarios.
Data Source
AI summary
A method and apparatus for upgrading libraries in a source code program by evaluating libraries in the source code program for predetermined selection criteria specifying library performance limitations to identify at least a first library which does not meet the plurality of predetermined selection criteria and then identifying a first alternative library that is suitable for substitution for the first library so that the source code program may be automatically modified to replace the first library with the first alternative library, thereby generating a modified source code program having an upgraded library functionality.