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Inferring test results for dynamic software product lines

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
  • Bruno Cafeo
  • Joost Noppen
  • Fabiano Ferrari
  • Ruzanna Chitchyan
  • Awais Rashid
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Publication date2011
Host publicationESEC/FSE '11 Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
Place of PublicationNew York
PublisherACM Press
Pages500-503
Number of pages4
ISBN (print)978-1-4503-0443-6
<mark>Original language</mark>English
EventSIGSOFT/FSE'11 19th ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE-19) and ESEC'11: 13rd European Software Engineering Conference (ESEC-13) - Szeged, Hungary
Duration: 5/09/20119/09/2011

Conference

ConferenceSIGSOFT/FSE'11 19th ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE-19) and ESEC'11: 13rd European Software Engineering Conference (ESEC-13)
Country/TerritoryHungary
CitySzeged
Period5/09/119/09/11

Conference

ConferenceSIGSOFT/FSE'11 19th ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE-19) and ESEC'11: 13rd European Software Engineering Conference (ESEC-13)
Country/TerritoryHungary
CitySzeged
Period5/09/119/09/11

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.