突变分析作为一种黑盒检测技术的有效性

T. Murnane, K. Reed
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引用次数: 57

摘要

突变测试技术是众所周知的,其中测试的有效性是通过创建语句发生突变的程序的变体来确定的。虽然具有相当大的理论价值,但该技术需要昂贵的工具,并且计算成本很高。即使是简单的程序也会产生大量的“突变体”。最近,有人提议将这个概念应用到基于规范的(黑盒)测试中。建议是通过系统地用与另一部分相关的数据项替换与规范的特定部分相关的数据项来生成测试用例。如果将规范视为生成一种描述有效输入集的语言,则突变过程旨在生成语法上有效和无效的语句。不管它们在规范方面是否“正确”,它们都可以以通常的(黑盒)方式用于测试程序。为了使这种方法具有实用价值,它必须生成其他流行的黑盒测试生成方法无法生成的测试用例。本文报告了一个案例研究,涉及基于突变的黑盒测试应用于两个不同类型的程序。测试用例也是使用等价类测试生成的。边界值测试方法。检查来自每种方法的测试用例,以判断重叠并评估生成的附加用例的价值。结果发现,对于数据审查程序,只有不到20%的突变测试用例是由其他两种方法生成的,而对于统计分析程序,则为75%。本文分析了这些结果,并提出了基于突变的测试用例生成可能有效的规范类别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the effectiveness of mutation analysis as a black box testing technique
The technique of mutation testing, in which the effectiveness of tests is determined by creating variants of a program in which statements are mutated, is well known.. Whilst of considerable theoretical interest, the technique requires costly tools and is computationally expensive. Very large numbers of 'mutants' can be generated for even simple programs. More recently, it has been proposed that the concept be applied to specification based (black box) testing. The proposal is to generate test cases by systematically replacing data items relevant to a particular part of a specification with a data item relevant to another. If the specification is considered as generating a language that describes the set of valid inputs, then the mutation process is intended to generate syntactically valid and invalid statements. Irrespective of their 'correctness' in terms of the specification, these can then be used to test a program in the usual (black box) manner. For this approach to have practical value it must produce test cases that would not be generated by other popular black box test generation approaches. The paper reports a case study involving the application of mutation based black box testing to two programs of different types. Test cases were also generated using equivalence class testing. and boundary value testing approaches. The test cases from each method were examined to judge the overlap and to assess the value of the additional cases generated. It was found that less than 20% of the mutation test cases for a data-vetting program were generated by the other two methods, as against 75% for a statistical analysis program. The paper analyses these results and suggests classes of specifications for which mutation based test-case generation may be effective.
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