Towards Fault Localization via Probabilistic Software Modeling
This addresses the challenge of precise fault localization for software developers, though it appears incremental as it builds on existing methods.
The paper tackles the problem of automatically pinpointing bug locations in software, proposing Probabilistic Software Modeling (PSM) to analyze program structure and behavior, with results indicating it is a robust framework for accurate fault localization.
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.