Carving Information Sources to Drive Search-Based Crash Reproduction and Test Case Generation

P. Derakhshanfar

Research output: ThesisDissertation (TU Delft)

217 Downloads (Pure)


Software testing is one of the essential and expensive tasks in software development. Hence, many approaches were introduced to automate different software testing tasks. Among these techniques, search-based test generation techniques have been vastly applied in real-world cases and have shown promising results. These strategies apply search-based methods for generating tests according to various test criteria such as line and branch coverage. In this thesis, we introduce new search objectives and techniques using various knowledge carved from resources like source code, hand-written test cases, and execution logs. These novel search objectives and approaches (i) improve the state-of-the-art in search-based crash reproduction, (ii) present a new search-based approach to generate class-integration tests covering interactions between two given classes., and (iii) introduce two new search objectives for covering common/uncommon execution patterns observed during the software production.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
  • Zaidman, A.E., Supervisor
  • van Deursen, A., Supervisor
  • Panichella, A., Advisor
Award date22 Apr 2021
Print ISBNs978-94-6421-312-6
Publication statusPublished - 2021


  • Search-based Software Testing
  • Crash Reproduction
  • Class Integration Testing
  • Carving Information Sources

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