Prioritized static slicing and its application to fault localization

• Published in: The Journal of systems and software Vol. 114; pp. 38 - 53
• Main Authors: Zhang, Yiji, Santelices, Raul
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01.04.2016; Elsevier Sequoia S.A
• Subjects: Computer programs; Debugging; Dependence analysis; Dynamical systems; Dynamics; Effectiveness studies; Fault localization; Fault location; Faults; Java; Java (programming language); Localization; Probabilistic slicing; Program analysis; Programming languages; Slicing; Software; Software engineering; Static slicing; Thin slicing; Fault localization; Dependence analysis; Probabilistic slicing; Program analysis; Thin slicing; Static slicing
• ISSN: 0164-1212; 1873-1228
• DOI: 10.1016/j.jss.2015.10.052

•We build a model PrioSlice that prioritizes statements in a static slice.•Not all statements in a static slice are equally likely to propagate effects.•Some data dependencies are more likely to occur than others.•Control dependencies are less likely than data dependencies to propagate effects.•PrioSlice helps localize faults more effectively than other static-slicing methods. Static slicing is a popular program analysis used in software engineering to find which parts of a program affect other parts. Unfortunately, static slicing often produces large and imprecise results because of its conservative nature. Dynamic slicing can be an alternative in some cases, but it requires detailed runtime information that can be hard or impossible to obtain or re-create. This is often the case when users report bugs in deployed software. In this paper, we significantly improve the precision of static slicing through PrioSlice, a novel technique that exploits the insight that not all statements in a static slice are equally likely to affect another statement such as a failing point. PrioSlice first computes a probabilistic model of the dependencies in the program. In this model, some data dependencies are more likely to occur than others and control dependencies are less likely than data dependencies to propagate effects (e.g., errors). PrioSlice then traverses the program backwards, like static slicing, but in an order defined by the computed dependence probabilities. Our study of fault localization on various Java subjects indicates that PrioSlice can help localize faults much more effectively than existing static-slicing approaches.