• DocumentCode
    1862145
  • Title

    Effective Software Bug Localization Using Spectral Frequency Weighting Function

  • Author

    Lee, Hua Jie ; Naish, Lee ; Ramamohanarao, Kotagiri

  • Author_Institution
    Univ. of Melbourne, Melbourne, VIC, Australia
  • fYear
    2010
  • fDate
    19-23 July 2010
  • Firstpage
    218
  • Lastpage
    227
  • Abstract
    This paper presents an approach of bug localization using a frequency weighting function. In an existing approach, only binary information of execution count from test executions is used. Information of each program statement being executed and not executed by a particular test is used; indicated by 1 and 0 respectively. In our proposed approach, frequency execution count of each program statement executed by a respective test is used. We evaluate several well-known spectra metrics using our proposed approach and the existing approach (using binary information of execution count) on two test suites; Siemens Test Suite and Unix datasets. We show that the bug localization performance is improved by using our proposed approach. We conduct statistical test and show that the improved bug localization performance using our approach (using frequency execution count) is statistically significant than using the existing approach (using binary information of execution count).
  • Keywords
    program debugging; software metrics; statistical testing; Siemens test suite; Unix datasets; software bug localization; spectra metrics; spectral frequency weighting function; statistical test; Benchmark testing; Computer bugs; Debugging; Frequency measurement; Runtime; Software; Frequency Weighting Function; Program Spectra; Spectra Metrics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Software and Applications Conference (COMPSAC), 2010 IEEE 34th Annual
  • Conference_Location
    Seoul
  • ISSN
    0730-3157
  • Print_ISBN
    978-1-4244-7512-4
  • Electronic_ISBN
    0730-3157
  • Type

    conf

  • DOI
    10.1109/COMPSAC.2010.26
  • Filename
    5676260