一句话：提出面向回归测试套件的增量代码覆盖率分析，使代码变更后覆盖率计算高效且与RTS兼容。
代码覆盖率分析已被广泛用于开源与工业软件仓库的持续集成，以监控回归测试套件的充分性。然而覆盖率计算代价高昂，会在测试执行中引入显著开销；而且当代码变更只影响部分覆盖率数据时，重新收集整个测试套件的覆盖率通常没有必要。已有的回归测试选择（RTS）技术可以选择行为可能受代码变更影响的测试子集，但它们与代码覆盖率分析不兼容：简单执行RTS选出的测试只会得到不正确的覆盖率结果。本文围绕这一问题，研究面向回归测试套件的高效增量覆盖率分析，目标是在变更后高效更新覆盖率信息并保持结果正确。摘要未给出具体实现与实验评估。
Code coverage analysis has been widely adopted in the continuous integration of open-source and industry software repositories to monitor the adequacy of regression test suites. However, computing code coverage can be costly, introducing significant overhead during test execution. Plus, re-collecting code coverage for the entire test suite is usually unnecessary when only a part of the coverage data is affected by code changes. While regression test selection (RTS) techniques exist to select a subset of tests whose behaviors may be affected by code changes, they are not compatible with code coverage analysis techniques---that is, simply executing RTS-selected tests leads to incorrect code coverage results.
DOI 原文 ·
@inproceedings{paperbot8419,
title = {Efficient Incremental Code Coverage Analysis for Regression Test Suites},
author = {Jiale Amber Wang and Kaiyuan Wang and Pengyu Nie},
booktitle = {ASE},
year = {2024},
doi = {10.1145/3691620.3695551}
}