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Practical Automatic Lightweight Nondeterminism and Flaky Test Detection and Debugging for Python

机译:Python的实用自动轻量级无限制和胶版测试检测和调试

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A critically important, but surprisingly neglected, aspect of system reliability is system predictability. Many soft-ware systems are implemented using mechanisms (unsafe languages, concurrency, caching, stochastic algorithms, environmental dependencies) that can introduce unexpected and unwanted behavioral nondeterminism. Such nondeterministic behavior can result in software bugs and flaky tests as well as causing problems for test reduction, differential testing, and automated regression test generation. We show that lightweight techniques, requiring little effort on the part of developers, can extend an existing testing system to allow detection and debugging of nondeterminism. We show how to make delta-debugging effective for probabilistic faults in general, and that our methods can improve mutation score by 6% for a strong, full differential test harness for a widely used mock file system.
机译:一个批判性重要的,但令人惊讶地被忽视,系统可靠性方面是系统的可预测性。许多软件系统是使用机制(不安全的语言,并发,缓存,随机算法,环境依赖性)实现意外和不需要的行为非季度的机制。这种非叛徒的行为可能导致软件错误和荧光测试以及导致测试减少,差异测试和自动回归测试生成问题。我们展示了轻量级技术,需要在开发人员的一部分内部努力,可以扩展现有的测试系统,以允许检测和调试非法确定。我们展示了如何使Delta-Debugging一般有效地对概率故障,并且我们的方法可以为广泛使用的模拟文件系统进行强大的全差分测试线束提高突变得分6%。

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