Managing software quality through a hybrid defect content and effectiveness model

ABSTRACT

Quality assurance (QA) plays a crucial role in today's software development. However, methods and models proposed in literature to support QA management suffer from several drawbacks. Many are specialized to certain activities like system test or inspections. They commonly support only one application purpose, e.g., planning or controlling, and are often applicable only after measurement data has been collected for several historical applications. To overcome these drawbacks, we developed a method that can be applied to QA activities during any phase, and which supports comprehensive quality management related tasks: improvement, planning, and controlling. To be applicable in practice, the method combines the available measurement data with expert judgment to build context-specific models. In addition, the method provides early benefits, while motivating the collection of measurement data by presenting possible improvement directions. The paper presents the general concepts behind the method and research questions to be answered in upcoming empirical studies.

REFERENCES

• 1: NIST: The economic impacts of inadequate infrastructure for software quality, 2002.
• 2: Jef Jacobs , Jan van Moll , Rob Kusters , Jos Trienekens , Aarnout Brombacher, Identification of factors that influence defect injection and detection in development of software intensive products, Information and Software Technology, v.49 n.7, p.774-789, July, 2007 [doi>10.1016/j.infsof.2006.09.002]
• 3: S. Chulani, B. Boehm, Modeling software defect introduction and removal: COQUALMO, University of Southern California Center for Software Engineering, USC-CSE Technical Report 99-510, 1999.
• 4: Stefan Wagner, A model and sensitivity analysis of the quality economics of defect-detection techniques, Proceedings of the 2006 international symposium on Software testing and analysis, July 17-20, 2006, Portland, Maine, USA [doi>10.1145/1146238.1146247]
• 5: M. R. Lyu, Encyclopedia of Software Engineering. John Wiley & Sons, chapter Software Reliabiliy Theory, 2002.
• 6: Lionel C. Briand , Khaled El Emam , Bernd Freimut , Oliver, Quantitative Evaluation of Capture-Recapture Models to Control Software Inspections, Proceedings of the Eighth International Symposium on Software Reliability Engineering (ISSRE '97), p.234, November 02-05, 1997
• 7: Lionel C. Briand , Bernd Freimut , Ferdinand Vollei, Using multiple adaptive regression splines to support decision making in code inspections, Journal of Systems and Software, v.73 n.2, p.205-217, October 2004 [doi>10.1016/j.jss.2004.01.015]
• 8: L. Briand, K. El Emam, F. Bomarius, COBRA: A Hybrid Method for Software Cost Estimation, Benchmarking, and Risk Assessment, ISERN-97-24, 1998.
• 9: Stephen H. Kan, Metrics and Models in Software Quality Engineering, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 2002
• 10: Bernd Freimut , Christian Denger , Markus Ketterer, An Industrial Case Study of Implementing and Validating Defect Classification for Process Improvement and Quality Management, Proceedings of the 11th IEEE International Software Metrics Symposium, p.19, September 19-22, 2005 [doi>10.1109/METRICS.2005.10]
• 11: M. Kläs, H. Nakao, F. Elberzhager, J. Münch, Predicting Defect Content and Quality Assurance Effectiveness by Combining Expert Judgment and Defect Data - A Case Study. Accepted at 19th IEEE International Symposium on Software Reliability, Nov. 2008.

INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING
      D.2.9 Management
          Subjects: Software quality assurance (SQA)

General Terms:
Experimentation, Management, Measurement, Reliability

Keywords:
defect content estimation, defect prediction, expert estimation, quality assurance effectiveness, quality assurance strategy, quality management