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A Systematic Literature Review on Prioritizing Software Test Cases Using Markov Chains

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Testing Software and Systems (ICTSS 2023)

Abstract

Software Testing is a costly activity since the size of the test case set tends to increase as the construction of the software evolves. Test Case Prioritization (TCP) can reduce the effort and cost of software testing. TCP is an activity where a subset of the existing test cases is selected in order to maximize the possibility of finding defects. On the other hand, Markov chains representing a system, when solved, can present the occupation time of each of their states. The idea is to use such information and associate priority to those test cases that consist of states with the highest probabilities. This journal-first paper provides an overview of a systematic survey of the state-of-the-art to identify and understand key initiatives for using Markov chains in TCP.

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References

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Acknowledgements

The authors acknowledge the support of the MUR (Italy) Department of Excellence 2023 - 2027 for GSSI.

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Correspondence to L. Rebelo .

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Barbosa, G., Souza, É., Rebelo, L., Silva, M., Balera, J., Vijaykumar, N. (2023). A Systematic Literature Review on Prioritizing Software Test Cases Using Markov Chains. In: Bonfanti, S., Gargantini, A., Salvaneschi, P. (eds) Testing Software and Systems. ICTSS 2023. Lecture Notes in Computer Science, vol 14131. Springer, Cham. https://doi.org/10.1007/978-3-031-43240-8_20

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  • DOI: https://doi.org/10.1007/978-3-031-43240-8_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43239-2

  • Online ISBN: 978-3-031-43240-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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