Software testing helps developers to identify bugs. However, awareness of bugs is only the first step. Finding and correcting the faulty program components is equally hard and essential for high-quality software. Fault localization automatically pinpoints the location of an existing bug in a program. It is a hard problem, and existing methods are not yet precise enough for widespread industrial adoption. We propose fault localization via Probabilistic Software Modeling (PSM). PSM analyzes the structure and behavior of a program and synthesizes a network of Probabilistic Models (PMs). Each PM models a method with its inputs and outputs and is capable of evaluating the likelihood of runtime data. We use this likelihood evaluation to find fault locations and their impact on dependent code elements. Results indicate that PSM is a robust framework for accurate fault localization.

中文翻译：

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通过概率软件建模实现故障定位

软件测试可帮助开发人员识别错误。然而，意识到错误只是第一步。查找和纠正有问题的程序组件对于高质量软件来说同样困难且必不可少。故障定位会自动查明程序中现有错误的位置。这是一个难题，现有的方法还不够精确，无法在工业上广泛采用。我们建议通过概率软件建模 (PSM) 进行故障定位。PSM 分析程序的结构和行为并合成概率模型 (PM) 网络。每个 PM 对其输入和输出进行建模，并能够评估运行时数据的可能性。我们使用这种可能性评估来查找故障位置及其对相关代码元素的影响。