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Adaptive Coverage and Operational Profile-Based Testing for Reliability Improvement

机译：自适应覆盖和基于操作配置文件的测试，以提高可靠性

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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.
机译：我们介绍covrel，这是一种基于操作配置文件和覆盖范围频谱的结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。基于操作配置文件的测试是一种黑盒技术，它选择对操作中的故障概率有最大影响的测试用例，因此，当可靠性成为主要关注点时，它被认为非常适合。程序频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的驱动思想是通过基于计数频谱的白盒覆盖度量值来补充操作配置文件信息，以便动态选择最有效的测试用例以提高可靠性。特别是，我们偏向那些覆盖频率较低的实体基于操作配置文件的测试选择。我们通过对软件测试研究中常用的4个主题的18个版本的实验进行实验来评估该方法，并将结果与​​传统的操作和覆盖测试进行比较。结果表明，以组合的自适应方式利用运营和覆盖数据实际上在可靠性方面有所回报，在超过80％的情况下，covrel克服了传统的运营测试。

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