Defect categorization: making use of a decade of widely varying historical data

  • Authors:

  • Carolyn B. Seaman;Forrest Shull;Myrna Regardie;Denis Elbert;Raimund L. Feldmann;Yuepu Guo;Sally Godfrey

  • Affiliations:

  • Fraunhofer Center for Experimental Software Engineering and University of Maryland Baltimore County, College Park, MD, USA;Fraunhofer Center for Experimental Software Engineering, College Park, MD, USA;Fraunhofer Center for Experimental Software Engineering, College Park, MD, USA;Fraunhofer Center for Experimental Software Engineering, College Park, MD, USA;Fraunhofer Center for Experimental Software Engineering, College Park, MD, USA;University of Maryland Baltimore County, Baltimore, MD, USA;NASA Goddard Space Flight Center, Greenbelt, MD, USA

  • Venue:
  • Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
  • Year:
  • 2008

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Abstract

This paper describes our experience in aggregating a number of historical datasets containing inspection defect data using different categorization schemes. Our goal was to make use of the historical data by creating models to guide future development projects. We describe our approach to reconciling the different choices used in the historical datasets to categorize defects, and the challenges we faced. We also present a set of recommendations for others involved in classifying defects.