• DocumentCode
    1705823
  • Title

    Guiding Testing Activities by Predicting Defect-Prone Parts Using Product and Inspection Metrics

  • Author

    Elberzhager, Frank ; Kremer, Stephan ; Münch, Jürgen ; Assmann, Danilo

  • Author_Institution
    Fraunhofer IESE, Kaiserslautern, Germany
  • fYear
    2012
  • Firstpage
    406
  • Lastpage
    413
  • Abstract
    Product metrics, such as size or complexity, are often used to identify defect-prone parts or to focus quality assurance activities. In contrast, quality information that is available early, such as information provided by inspections, is usually not used. Currently, only little experience is documented in the literature on whether data from early defect detection activities can support the identification of defect prone parts later in the development process. This article compares selected product and inspection metrics commonly used to predict defect-prone parts. Based on initial experience from two case studies performed in different environments, the suitability of different metrics for predicting defect-prone parts is illustrated. These studies revealed that inspection defect data seems to be a suitable predictor, and a combination of certain inspection and product metrics led to the best prioritizations in our contexts.
  • Keywords
    inspection; program testing; quality assurance; software metrics; software quality; defect-prone parts identification; defect-prone parts prediction; early defect detection activities; inspection defect data; inspection metrics; product metrics; quality assurance; quality information; Complexity theory; Context; Focusing; Inspection; Measurement; Quality assurance; Testing; case study; comparison; focusing; inspection metrics; product metrics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Advanced Applications (SEAA), 2012 38th EUROMICRO Conference on
  • Conference_Location
    Cesme, Izmir
  • Print_ISBN
    978-1-4673-2451-9
  • Type

    conf

  • DOI
    10.1109/SEAA.2012.30
  • Filename
    6328182