Smoke Test Planning using Answer Set Programming

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Smoke Test Planning using Answer Set Programming

Tobias PhilippTobias Philipp,  Valentin RolandValentin Roland,  Lukas SchweizerLukas Schweizer
Smoke Test Planning using Answer Set Programming


Tobias Philipp, Valentin Roland, Lukas Schweizer
Smoke Test Planning using Answer Set Programming
International Journal of Interactive Multimedia and Artificial Intelligence, 6(5):57--65, February 2021
  • KurzfassungAbstract
    Smoke testing is an important method to increase stability and reliability of hardware-dependent systems. Due to concurrent access to the same physical resource and the impracticality of the use of virtualization, smoke testing requires some form of planning. In this paper, we propose to decompose test cases in terms of atomic actions consisting of preconditions and effects. We present a solution based on answer set programming with multi-shot solving that automatically generates short parallel test plans. Experiments suggest that the approach is feasible for non-inherently sequential test cases and scales up to thousands of test cases.
  • Weitere Informationen unter:Further Information: Link
  • Forschungsgruppe:Research Group: Computational LogicComputational Logic
@article{PRS2021,
  author  = {Tobias Philipp and Valentin Roland and Lukas Schweizer},
  title   = {Smoke Test Planning using Answer Set Programming},
  journal = {International Journal of Interactive Multimedia and Artificial
             Intelligence},
  volume  = {6},
  number  = {5},
  year    = {2021},
  month   = {February},
  pages   = {57--65},
  doi     = {10.9781/ijimai.2021.02.003}
}