Experiences and results from initiating field defect prediction and product test prioritization efforts at ABB Inc.

  • Authors:

  • Paul Luo Li;James Herbsleb;Mary Shaw;Brian Robinson

  • Affiliations:

  • Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;ABB, Inc, Wickliffe, OH

  • Venue:
  • Proceedings of the 28th international conference on Software engineering
  • Year:
  • 2006

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Abstract

Quantitatively-based risk management can reduce the risks associated with field defects for both software producers and software consumers. In this paper, we report experiences and results from initiating risk-management activities at a large systems development organization. The initiated activities aim to improve product testing (system/integration testing), to improve maintenance resource allocation, and to plan for future process improvements. The experiences we report address practical issues not commonly addressed in research studies: how to select an appropriate modeling method for product testing prioritization and process improvement planning, how to evaluate accuracy of predictions across multiple releases in time, and how to conduct analysis with incomplete information. In addition, we report initial empirical results for two systems with 13 and 15 releases. We present prioritization of configurations to guide product testing, field defect predictions within the first year of deployment to aid maintenance resource allocation, and important predictors across both systems to guide process improvement planning. Our results and experiences are steps towards quantitatively-based risk management.