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    Explaining software failures by cascade fault localization

    Access Status
    Fulltext not available
    Authors
    Yi, Q.
    Yang, Z.
    Liu, Jian
    Zhao, C.
    Wang, C.
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Yi, Q. and Yang, Z. and Liu, J. and Zhao, C. and Wang, C. 2015. Explaining software failures by cascade fault localization. ACM Transactions on Design Automation of Electronic Systems. 20 (3).
    Source Title
    ACM Transactions on Design Automation of Electronic Systems
    DOI
    10.1145/2738038
    ISSN
    1084-4309
    School
    WASM: Minerals, Energy and Chemical Engineering (WASM-MECE)
    URI
    http://hdl.handle.net/20.500.11937/72416
    Collection
    • Curtin Research Publications
    Abstract

    © 2015 ACM. During software debugging, a significant amount of effort is required for programmers to identify the root cause of a manifested failure. In this article, we propose a cascade fault localization method to help speed up this labor-intensive process via a combination of weakest precondition computation and constraint solving. Our approach produces a cause tree, where each node is a potential cause of the failure and each edge represents a casual relationship between two causes. There are two main contributions of this article that differentiate our approach from existing methods. First, our method systematically computes all potential causes of a failure and augments each cause with a proper context for ease of comprehension by the user. Second, our method organizes the potential causes in a tree structure to enable on-the-fly pruning based on domain knowledge and feedback from the user. We have implemented our new method in a software tool called CaFL, which builds upon the LLVM compiler and KLEE symbolic virtual machine. We have conducted experiments on a large set of public benchmarks, including real applications from GNU Coreutils and Busybox. Our results show that in most cases the user has to examine only a small fraction of the execution trace before identifying the root cause of the failure.

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