• DocumentCode
    2587484
  • Title

    Classification of Software Defect Detected by Black-Box Testing: An Empirical Study

  • Author

    Li, Ning ; Li, Zhanhuai ; Sun, Xiling

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Northwestern Polytech. Univ., Xi´´an, China
  • Volume
    2
  • fYear
    2010
  • fDate
    19-20 Dec. 2010
  • Firstpage
    234
  • Lastpage
    240
  • Abstract
    Software defects which are detected by black box testing (called black-box defect) are very large due to the wide use of black-box testing, but we could not find a defect classification which is specifically applicable to them in existing defect classifications. In this paper, we present a new defect classification scheme named ODC-BD (Orthogonal Defect Classification for Black-box Defect), and we list the detailed values of every attribute in ODC-BD, especially the 300 detailed black-box defect type. We aim to help black-box defect analyzers and black-box testers improve their analysis and testing efficiency. The classification study is based on 1860 black-box defects collected from 39 industry projects and 2 open source projects. Furthermore, two empirical studies are included to validate the use of our ODC-BD. The results show that our ODC-BD can improve the efficiency of black-box testing and black-box defect analysis.
  • Keywords
    pattern classification; program testing; software maintenance; ODC-BD; black-box testing; industry project; open source project; orthogonal defect classification; software defect detection; testing efficiency; Data mining; Inspection; Software engineering; Testing; Unified modeling language; Usability; Orthogonal Defect Classification (ODC); black-box testing; defect analysis; defect category; defect classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering (WCSE), 2010 Second World Congress on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9287-9
  • Type

    conf

  • DOI
    10.1109/WCSE.2010.28
  • Filename
    5718384