Locating faults using multiple spectra-specific models

  • Authors:

  • Kai Yu;Mengxiang Lin;Qing Gao;Hui Zhang;Xiangyu Zhang

  • Affiliations:

  • Beihang University, P. R. China;Beihang University, P. R. China;Beihang University, P. R. China;Beihang University, P. R. China;Beihang University, P. R. China

  • Venue:
  • Proceedings of the 2011 ACM Symposium on Applied Computing
  • Year:
  • 2011

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Abstract

Spectra-based fault localization (SFL) techniques have brought encouraging results and a variety of program spectra have been proposed to locate faults. Different types of abnormal behaviors may be revealed by different kinds of spectra. Compared to techniques using single spectra type, techniques combining multiple types of spectra try to leverage the strengths of the constituent types. However, in the presence of multiple kinds of spectra, how to select adequate spectra type and build appropriate models need further investigation. In this paper, we propose an SFL technique LOUPE, which uses multiple spectra-specific models. Both control and data dependences are introduced to capture unusual behaviors of faults. In the stage of suspiciousness modeling, in contrast with previous studies, we build different models to evaluate the suspiciousness of statements for each spectra type respectively. Finally, since the fault type is unknown in advance, suspiciousness scores are calculated based on the two models. We evaluate LOUPE on the Siemens benchmark and experimental results show that our technique is promising.