Orthogonal Defect Classification-A Concept for In-Process Measurements

  • Authors:

  • Ram Chillarege;Inderpal S. Bhandari;Jarir K. Chaar;Michael J. Halliday;Diane S. Moebus;Bonnie K. Ray;Man-Yuen Wong

  • Affiliations:

  • IBM T. J. Watson Research Center, Yorktown Heights, NY;IBM T. J. Watson Research Center, Yorktown Heights, NY;IBM T. J. Watson Research Center, Yorktown Heights, NY;IBM T. J. Watson Research Center, Yorktown Heights, NY;IBM Mid-Hudson Valley Programming Lab, Wappinger Falls, NY;IBM T. J. Watson Research Center, Yorktown Heights, NY;IBM T. J. Watson Research Center, Yorktown Heights, NY

  • Venue:
  • IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
  • Year:
  • 1992

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Abstract

Orthogonal defect classification (ODC), a concept that enables in-process feedback to software developers by extracting signatures on the development process from defects, is described. The ideas are evolved from an earlier finding that demonstrates the use of semantic information from defects to extract cause-effect relationships in the development process. This finding is leveraged to develop a systematic framework for building measurement and analysis methods. The authors define ODC and discuss the necessary and sufficient conditions required to provide feedback to a developer; illustrate the use of the defect type distribution to measure the progress of a product through a process; illustrate the use of the defect trigger distribution to evaluate the effectiveness and eventually the completeness of verification processes such as inspection or testing; provides sample results from pilot projects using ODC; and open the doors to a wide variety of analysis techniques for providing effective and fast feedback based on the concepts of ODC.