An Approach to Test Data Generation for Killing Multiple Mutants

Ming-Hao Liu, You-Feng Gao, Jinhui Shan, Jiang-Hong Liu, Lu Zhang, Jiasu Sun
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引用次数: 34

Abstract

Software testing is an important technique for assurance of software quality. Mutation testing has been identified as a powerful fault-based technique for unit testing, and there has been some research on automatic generation of test data for mutation testing. However, existing approaches to this kind of test data generation usually generate test data according to one mutant at one time. Thus, more test data that are needed for achieving a given mutation score. In this paper, we propose a new approach to generating one test data according to multiple mutants that are mutated at the same location at one time. Thus, our approach can generate smaller test suite that can achieve the same mutation testing score. To evaluate our approach, we implemented a prototype tool based on our approach and carried out some preliminary experiments. The experimental results show that our approach is more cost-effective
一种杀死多突变体的测试数据生成方法
软件测试是保证软件质量的一项重要技术。突变测试被认为是一种功能强大的基于故障的单元测试技术,针对突变测试数据的自动生成已经有了一些研究。然而,现有的这种测试数据生成方法通常是一次根据一个突变体生成测试数据。因此,需要更多的测试数据来获得给定的突变分数。在本文中,我们提出了一种根据同时在同一位置发生突变的多个突变体生成一个测试数据的新方法。因此,我们的方法可以生成更小的测试套件,可以达到相同的突变测试分数。为了评估我们的方法,我们基于我们的方法实现了一个原型工具,并进行了一些初步的实验。实验结果表明,该方法具有较高的成本效益
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