Are change metrics good predictors for an evolving software product line?

  • Authors:

  • Sandeep Krishnan;Chris Strasburg;Robyn R. Lutz;Katerina Goševa-Popstojanova

  • Affiliations:

  • Iowa State University, Ames, IA;Iowa State University & Ames Laboratory;Iowa State University & JPL/Caltech;West Virginia University, Morgantown, WV

  • Venue:
  • Proceedings of the 7th International Conference on Predictive Models in Software Engineering
  • Year:
  • 2011

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Abstract

Background: Previous research on three years of early data for an Eclipse product identified some predictors of failure-prone files that work well for that data set. Additionally, Eclipse has been used to explore characteristics of product line software in previous research. Aims: To assess whether change metrics are good predictors of failure-prone files over time for the family of products in the evolving Eclipse product line. Method: We repeat, to the extent possible, the decision tree portion of the prior study to assess our ability to replicate the method, and then extend it by including four more recent years of data. We compare the most prominent predictors with the previous study's results. We then look at the data for three additional Eclipse products as they evolved over time. We explore whether the set of good predictors change over time for one product and whether the set differs among products. Results: We find that change metrics are consistently good and incrementally better predictors across the evolving products in Eclipse. There is also some consistency regarding which change metrics are the best predictors. Conclusion: Change metrics are good predictors for failure-prone files for the Eclipse product line. A small subset of these change metrics is fairly stable and consistent across products and releases.