Fuzzy Clustering the Backward Dynamic Slices of Programs to Identify the Origins of Failure

  • Saeed Parsa
  • Farzaneh Zareie
  • Mojtaba Vahidi-Asl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6630)


In this paper a new technique for identifying the origins of program failure is presented. To achieve this, the outstanding features of both statistical debugging and dynamic slicing techniques are combined. The proposed Fuzzy-Slice technique, computes the full backward dynamic slice of variables used in output statement of a given program in several failing and passing executions. According to the statements presented in the slice of an execution, each run could be converted into an execution point within Euclidean space, namely execution space. Using fuzzy clustering technique, different program execution paths are identified and the fault relevant statements are ranked according to their presence in different clusters. The novel scoring method for identifying fault relevant statements considers the observation of a statement in all execution paths. The promising results on Siemens test suite reveal the high accuracy and precision of the proposed Fuzzy-Slice technique.


Software Debugging Fuzzy Clustering Backward Dynamic Slicing Failure 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Saeed Parsa
    • 1
  • Farzaneh Zareie
    • 1
  • Mojtaba Vahidi-Asl
    • 1
  1. 1.Department of Software EngineeringIran University of Science and TechnologyTehranIran

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