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Debugging and test case generation using constraints and mutations

机译:使用约束和变异进行调试和测试用例生成

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摘要

The automation of debugging, i.e., fault localization, is an old but still open challenge in computer science. There are a number of at least partial solutions reported in literature. Some of them rely on basic concepts of AI like model-based debugging or debugging based on constraints. In this paper we focus on constraint-based debugging, provide a detailed formal introduction of the basic ideas and concepts, and finally state the automated debugging challenge as a constraint satisfaction problem. Although the proposed solution is general, the approach is more applicable to restricted programs like the one used in control. Furthermore, we introduce an extension of previous work that is based on program mutations and distinguishing test cases and discuss empirical results indicating the applicability of the approach. With the introduced extensions we obtain reductions in the number of diagnosis candidates of more than 50 %.
机译:调试的自动化,即故障定位,是计算机科学中的旧的但仍是开放的挑战。文献中报道了许多至少部分解决方案。其中一些依赖于AI的基本概念,例如基于模型的调试或基于约束的调试。在本文中,我们专注于基于约束的调试,对基本思想和概念进行了详细的形式化介绍,最后将自动化调试的挑战描述为约束满足问题。尽管提出的解决方案是通用的,但该方法更适用于受限制的程序,例如用于控制的程序。此外,我们介绍了基于程序变异和区分测试用例的先前工作的扩展,并讨论了表明该方法适用性的经验结果。通过引入的扩展,我们可以将诊断候选对象的数量减少50%以上。

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