一句话：提出局部搜索采样方法 LS-Sampling，以更小测试套件更快实现更高的 t-wise 覆盖。
高度可配置软件系统的测试需要高 t-wise 覆盖来保证充分性，但现有方法为达到高成对覆盖往往需生成大规模测试套件且耗时较长。本文提出基于局部搜索的采样方法 LS-Sampling，用于生成小规模测试套件以实现高 t-wise 覆盖。作者在大量来自真实高度可配置系统的公开基准上开展实验，并与当前最优方法比较。结果表明，LS-Sampling 取得更高的 2-wise 和 3-wise 覆盖：仅用 100 个测试用例（比最优对比方法小 90%）平均达到 99.64% 的 2-wise 覆盖和 97.87% 的 3-wise 覆盖，且平均执行时间不足一分钟。
There has been a rapidly increasing demand for developing highly configurable software systems, which urgently calls for effective testing methods. In practice, t-wise coverage has been widely recognized as a useful metric to evaluate the quality of a test suite for testing highly configurable software systems, and achieving high t-wise coverage is important for ensuring test adequacy. However, state-of-the-art methods usually cost a fairly long time to generate large test suites for high pairwise coverage (i.e., 2-wise coverage), which would lead to ineffective and inefficient testing of highly configurable software systems. In this paper, we propose a novel local search based sampling approach dubbed LS-Sampling for achieving high t-wise coverage. Extensive experiments on a large number of public benchmarks, which are collected from real-world, highly configurable software systems, show that LS-Sampling achieves higher 2-wise and 3-wise coverage than the current state of the art. LS-Sampling is effective, since on average it achieves the 2-wise coverage of 99.64% and the 3-wise coverage of 97.87% through generating a small test suite consisting of only 100 test cases (90% smaller than the test suites generated by its state-of-the-art competitors). Furthermore, LS-Sampling is efficient, since it only requires an average execution time of less than one minute to generate a test suite with high 2-wise and 3-wise coverage.
DOI 原文 ·
@inproceedings{paperbot6360,
title = {LS-sampling: an effective local search based sampling approach for achieving high t-wise coverage},
author = {Chuan Luo and Binqi Sun and Bo Qiao and Junjie Chen and Hongyu Zhang and Jinkun Lin and Qingwei Lin and Dongmei Zhang},
booktitle = {FSE},
year = {2021},
doi = {10.1145/3468264.3468622}
}