Marple

Author:

Le Wei1,Soffa Mary Lou2

Affiliation:

1. Rochester Institute of Technology

2. University of Virginia

Abstract

Generally, a fault is a property violation at a program point along some execution path. To obtain the path where a fault occurs, we can either run the program or manually identify the execution paths through code inspection. In both of the cases, only a very limited number of execution paths can be examined for a program. This article presents a static framework, Marple, that automatically detects path segments where a fault occurs at a whole program scale. An important contribution of the work is the design of a demand-driven analysis that effectively addresses scalability challenges faced by traditional path-sensitive fault detection. The techniques are made general via a specification language and an algorithm that automatically generates path-based analyses from specifications. The generality is achieved in handling both data- and control-centric faults as well as both liveness and safety properties, enabling the exploitation of fault interactions for diagnosis and efficiency. Our experimental results demonstrate the effectiveness of our techniques in detecting path segments of buffer overflows, integer violations, null-pointer dereferences, and memory leaks. Because we applied an interprocedural, path-sensitive analysis, our static fault detectors generally report better precision than the tools available for comparison. Our demand-driven analyses are shown scalable to deployed applications such as apache , putty , and ffmpeg .

Funder

Microsoft Research

Publisher

Association for Computing Machinery (ACM)

Subject

Software

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Compiler bug isolation via effective witness test program generation;Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2019-08-12

2. RARE: An Efficient Static Fault Detection Framework for Definition-Use Faults in Large Programs;IEEE Access;2018

3. Mining Patterns of Unsatisfiable Constraints to Detect Infeasible Paths;2015 IEEE/ACM 10th International Workshop on Automation of Software Test;2015-05

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