Short bio

Dr. Xavier Devroey is a postdoctoral researcher at the Software Engineering Research Group (SERG) of the Delft University of Technology. He is involved in the EU Software Testing AMPlification (STAMP) and the 3TU Big Software on the Run (BSR) projects. His main research interests are search-based and model-based software testing, test suite augmentation, DevOps, and variability-intensive systems.

He obtained his Master Degree in Computer Science from the University of Namur, Belgium, in June 2010. He worked as application developer for Atos Worldline, a large card payment company, for one year before starting a Ph.D. as teaching assistant in 2011 at the University of Namur. He defended his thesis entitled “Software Product Line Behavioural Model-Based Testing” in August 2017.

Ph.D. Thesis: Behavioural model-based testing of software product lines

Supervisors

  • Prof. Dr. Ing. Pierre-Yves Schobbens
  • Prof. Dr. Patrick Heymans

Description

Since the inception of Software Product Line (SPL) engineering, concerns about testing SPLs emerged. The large number of possible products that may be derived from a SPL induces an even larger set of test cases, which makes SPL testing a very challenging activity. In this thesis, we developed a testing framework to perform SPL behavioural model-based testing. We rely on Featured Transition Systems (FTSs), a compact formalism to rep- resent the behaviour of a SPL to perform various testing activities: test case selection and prioritization using structural coverage, dissimilarity, and statistical criteria; and mutation analysis using featured mutant models. The approaches have been implemented in an open-source Variability-Intensive Behavioural teSting framework (VIBeS) and evaluated on various models of different sizes, representing embedded systems and web-applications. Results demonstrate the applicability of FTSs to select/prioritize test cases and to perform mutation analysis, and confirm the relevance of combining variability models and behavioural models to enhance SPL model-based testing.