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Testing Real-Time Systems under Uncertainty

  • Alexandre David
  • Kim Guldstrand Larsen
  • Shuhao Li
  • Marius Mikucionis
  • Brian Nielsen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6957)

Abstract

Model-based testing is a promising technique for improving the quality of testing by automatically generating an efficient set of provably valid test cases from a system model. Testing embedded real-time systems is challenging because it must deal with timing, concurrency, processing and computation of complex mixed discrete and continuous signals, and limited observation and control. Whilst several techniques and tools have been proposed, few deals systematically with models capturing the indeterminacy resulting from concurrency, timing and limited observability and controllability. This paper proposes a number of model-based test generation principles and techniques that aim at efficient testing of timed systems under uncertainty.

Keywords

Test Purpose Winning Strategy Test Case Generation Partial Observability Conformance Testing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Alexandre David
    • 1
  • Kim Guldstrand Larsen
    • 1
  • Shuhao Li
    • 1
  • Marius Mikucionis
    • 1
  • Brian Nielsen
    • 1
  1. 1.Center for Embedded Software Systems (CISS)Aalborg UniversityAalborgDenmark

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