自适应覆盖和基于操作概要的可靠性改进测试

A. Bertolino, Breno Miranda, R. Pietrantuono, S. Russo
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引用次数: 17

摘要

我们介绍了covrel,一种基于操作概要和覆盖范围组合使用的自适应软件测试方法,其最终目标是提高被测程序的交付可靠性。基于操作概要文件的测试是一种黑盒技术,它选择对操作中失败概率影响最大的测试用例,因此,当可靠性是主要关注点时,它被认为非常适合。程序谱是根据程序执行时所涵盖的代码实体(例如,分支、语句、函数)来描述程序行为的特征。covrel的驱动思想是用基于计数谱的白盒覆盖度量来补充运行剖面信息,从而动态选择最有效的测试用例来提高可靠性。特别是,我们将基于操作概要文件的测试选择偏向于那些较少覆盖的实体。我们通过软件测试研究中常用的4个主题的18个版本的实验来评估该方法,并将结果与传统的操作测试和覆盖测试进行比较。结果表明,以组合自适应方式开发运行和覆盖数据实际上在可靠性提高方面是有回报的,在80%以上的情况下,covrel克服了常规的运行测试。
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Adaptive Coverage and Operational Profile-Based Testing for Reliability Improvement
We introduce covrel, an adaptive software testing approach based on the combined use of operational profile and coverage spectrum, with the ultimate goal of improving the delivered reliability of the program under test. Operational profile-based testing is a black-box technique that selects test cases having the largest impact on failure probability in operation, as such, it is considered well suited when reliability is a major concern. Program spectrum is a characterization of a program's behavior in terms of the code entities (e.g., branches, statements, functions) that are covered as the program executes. The driving idea of covrel is to complement operational profile information with white-box coverage measures based on count spectra, so as to dynamically select the most effective test cases for reliability improvement. In particular, we bias operational profile-based test selection towards those entities covered less frequently. We assess the approach by experiments with 18 versions from 4 subjects commonly used in software testing research, comparing results with traditional operational and coverage testing. Results show that exploiting operational and coverage data in a combined adaptive way actually pays in terms of reliability improvement, with covrel overcoming conventional operational testing in more than 80% of the cases.
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