Automated Test Prioritization via Code Change Impact Analysis
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Solution Overview
Problem
Modern software development methods face challenges in quickly identifying and fixing bugs, as bugs detected late in the development cycle are more difficult and time-consuming to resolve, highlighting the need for efficient automated testing techniques that focus on impacted areas of the codebase.
Innovation Solution
A method and system for automated software testing that maps test cases to lines in a codebase, determines impacted test cases based on change lists, prioritizes them using previous test results, and executes prioritized test cases to obtain new results, enabling focused testing and early bug detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all test cases are executed to ensure comprehensive testing, then testing coverage is improved, but testing time and resource consumption increase
Solution Approach 1:
The patent segments the test case execution process into two distinct phases: a prioritization phase that analyzes change lists and historical test results to rank test cases, and an execution phase that runs only the top-prioritized test cases. This segmentation allows the system to achieve efficient testing by separating the decision-making logic from the execution logic, thereby reducing overall testing time while maintaining focus on critical areas.
Solution Approach 2:
The patent performs preliminary actions by pre-calculating and storing the prioritization scores of all test cases based on historical data and change impact analysis before actual test execution. This preliminary prioritization enables the system to quickly identify and execute only the most relevant test cases without re-evaluating all test cases during the execution phase, significantly reducing testing time while maintaining comprehensive coverage of critical functionality.
2Productivity
If test cases are prioritized based on historical results, then bug detection efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements feedback mechanisms by continuously analyzing historical test results and using this information to dynamically adjust test case prioritization. The system feeds back the outcomes of previous test executions into the prioritization model, allowing it to learn from past bugs and focus future testing on areas most likely to reveal new issues. This feedback loop improves bug detection efficiency without requiring complex manual intervention.
Solution Approach 2:
The system performs self-service by automatically generating and updating test case prioritization based on its own historical test results and change list analysis. The prioritization engine uses the system's accumulated knowledge about which test cases have historically revealed bugs to automatically rank test cases, eliminating the need for external manual prioritization while keeping the system relatively simple through automated decision-making.
3Speed
If focused testing on impacted areas is implemented, then testing speed is improved, but testing thoroughness may be reduced
Solution Approach 1:
The patent applies local quality by assigning different prioritization weights to different test cases based on their specific characteristics and historical performance. Instead of treating all test cases uniformly, the system identifies test cases that are locally optimal for detecting bugs in specific areas of the codebase. This allows focused testing on high-impact areas while maintaining the capability to execute additional test cases if needed, balancing speed and thoroughness.
Data Source
AI summary
A method for automated software testing may include mapping test cases to lines in files in a codebase. Each test case covers one or more lines in one or more files and has corresponding test results. The method may further include obtaining a change list including one or more changes. Each change specifies a changed line in a changed file. The method may further include determining impacted test cases, based on the mapping and the change list, prioritizing the impacted test cases based, in part, on test results corresponding to each impacted test case, executing, based on the prioritization, one or more impacted test cases to obtain executed test cases, and obtaining, for each executed test case, new test results.