Inferring test results for dynamic software product lines

  • Authors:

  • Bruno B.P. Cafeo;Joost Noppen;Fabiano C. Ferrari;Ruzanna Chitchyan;Awais Rashid

  • Affiliations:

  • University of Sao Paulo, Soo Carlos, Brazil;University of East Anglia, Norwich, United Kingdom;Federal University of Sao Carlos, Sao Carlos, Brazil;Lancaster University, Lancaster, United Kingdom;Lancaster University, Lancaster, United Kingdom

  • Venue:
  • Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
  • Year:
  • 2011

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Abstract

Due to the very large number of configurations that can typically be derived from a Dynamic Software Product Line (DSPL), efficient and effective testing of such systems have become a major challenge for software developers. In particular, when a configuration needs to be deployed quickly due to rapid contextual changes (e.g., in an unfolding crisis), time constraints hinder the proper testing of such a configuration. In this paper, we propose to reduce the testing required of such DSPLs to a relevant subset of configurations. Whenever a need to adapt to an untested configuration is encountered, our approach determines the most similar tested configuration and reuses its test results to either obtain a coverage measure or infer a confidence degree for the new, untested configuration. We focus on providing these techniques for inference of structural testing results for DSPLs, which is supported by an early prototype implementation.