| 摘要: |
| 软件测试是一种广泛使用的软件质量保证手段. 变异测试是一种基于故障的软件测试方法, 广泛用于评估测试用例集的充分性与软件测试技术的有效性. 数量庞大的变异体导致变异测试的成本非常高. 提出一种数据流分析指导的变异体精简方法(DFSampling), 设计了启发式规则, 基于这些规则对随机选择技术与基于路径感知的变异体精简技术(PAMR)进行了改进. 采用经验研究的方式评估了DFSampling的有效性, 比较了DFSampling与随机选择技术、PAMR技术的有效性, 实验结果表明DFSampling是一种有效的变异体精简策略, 提高了变异测试的效率. |
| 关键词: 软件测试 变异测试 数据流分析 变异体精简 随机选择策略 |
| DOI：10.13328/j.cnki.jos.006291 |
| 分类号:TP311 |
| 基金项目:国家自然科学基金(61872039); 中国科学院软件研究所计算机科学国家重点实验室开放课题(SYSKF1803); 中央高校基本科研业务费专项(FRF-GF-19-019B). |
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| DFSampling: Mutant Reduction Technique Guided by Data Flow Analysis |
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SUN Chang-Ai1,2, WEI Xin-Jie1, LIU Zhen-Xian1, GONG Yun-Zhan3
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1.School of Computer & Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China;2.State Key Laboratory of Computer Science (Institute of Software, Chinese Academy of Sciences), Beijing 100190, China;3.Institute of Network Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
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| Abstract: |
| Software testing is a commonly used software quality assurance technique. Mutation testing is a fault-based software testing technique that is widely applied to evaluate the sufficiency of test suites and the effectiveness of software testing techniques. However, the cost of mutation testing is extremely high due to the large number of mutants. This study proposes a mutant reduction technique, DFSampling, guided by data flow analysis and designs three heuristic rules. The random selection technique and the path-aware mutant reduction technique (PAMR) are improved in line with these rules. An empirical study is conducted to evaluate the effectiveness of DFSampling and compare DFSampling with the random selection technique and the PAMR technique in terms of effectiveness. The experimental results show that DFSampling is an effective mutant reduction strategy, which can increase the efficiency of mutation testing. |
| Key words: software testing mutation testing data-flow analysis mutant reduction random selection strategy |
