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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Barbosa, G., de Souza, É.F., dos Santos, L.B.R., da Silva, M., Balera, J.M., Vijaykumar, N.L.: A systematic literature review on prioritizing software test cases using Markov chains. Inf. Softw. Technol. 147, 106902 (2022). https://doi.org/10.1016/j.infsof.2022.106902
Cai, K.Y.: Optimal software testing and adaptive software testing in the context of software cybernetics. Inf. Softw. Technol. 44(14), 841–855 (2002)
Devroey, X., et al.: Statistical prioritization for software product line testing: an experience report. Softw. Syst. Model. 16(1), 153–171 (2015)
Elbaum, S., Malishevsky, A.G., Rothermel, G.: Test case prioritization: a family of empirical studies. IEEE Trans. Software Eng. 28(2), 159–182 (2002)
Morozov, A., Ding, K., Chen, T., Janschek, K.: Test suite prioritization for efficient regression testing of model-based automotive software. In: 2017 International Conference on Software Analysis, Testing and Evolution (SATE), pp. 20–29 (2017)
Sayyari, F., Emadi, S.: Automated generation of software testing path based on ant colony. In: 2015 International Congress on Technology, Communication and Knowledge (ICTCK), pp. 435–440. IEEE (2015)
Walton, G., Poore, J.: Measuring complexity and coverage of software specifications. Inf. Softw. Technol. 42(12), 859–872 (2000)
Zhou, B., Okamura, H., Dohi, T.: Application of Markov chain Monte Carlo random testing to test case prioritization in regression testing. IEICE Trans. Inf. Syst. E95.D(9), 2219–2226 (2012)
Acknowledgements
The authors acknowledge the support of the MUR (Italy) Department of Excellence 2023 - 2027 for GSSI.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 IFIP International Federation for Information Processing
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-031-43240-8_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-43239-2
Online ISBN: 978-3-031-43240-8
eBook Packages: Computer ScienceComputer Science (R0)