Abstract
We report on early results in a long term project to apply learning-based testing (LBT) to evaluate the functional correctness of distributed systems and their robustness to injected faults. We present a case study of a commercial product for counter-party credit risk implemented as a distributed microservice architecture. We describe the experimental set-up, as well as test results. From this experiment, we draw some conclusions about prospects for future research in learning-based testing.
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Notes
- 1.
A fault is a triple consisting of a type, a location and a time [9].
References
Angluin, D.: Learning regular sets from queries and counterexamples. Inf. Comput. 75, 87–106 (1987)
Cimatti, A., Clarke, E.M., Giunchiglia, E., Giunchiglia, F., Pistore, M., Roveri, M., Sebastiani, R., Tacchella, A.: NuSMV 2: an OpenSource tool for symbolic model checking. In: Proceedings of International Conference on Computer-Aided Verification (CAV 2002) (2002)
Feng, L., Lundmark, S., Meinke, K., Niu, F., Sindhu, M.A., Wong, P.Y.H.: Case studies in learning-based testing. In: Yenigün, H., Yilmaz, C., Ulrich, A. (eds.) ICTSS 2013. LNCS, vol. 8254, pp. 164–179. Springer, Heidelberg (2013)
Fowler, M.: Microservices (2014). http://martinfowler.com/articles/microservices.html
Meinke, K., Sindhu, M.A.: Incremental learning-based testing for reactive systems. In: Gogolla, M., Wolff, B. (eds.) TAP 2011. LNCS, vol. 6706, pp. 134–151. Springer, Heidelberg (2011)
Meinke, K., Sindhu, M.: LBTest: a learning-based testing tool for reactive systems. In: Proceedings of Sixth International IEEE Conference on Software Testing, Verification and Validation (ICST 2013) (2013)
Niese, O.: An Integrated Approach to Testing Complex Systems. Ph.D. thesis, University of Dortmund (2003)
Shepperd, M., Bowes, D., Hall, T.: Researcher bias: the use of machine learning in software defect prediction. IEEE Trans. Software Eng. 40(6), 603–616 (2014)
Svenningson, R.: Model Implemented Fault-injection for Robustness Assessment. Licentiate Thesis, KTH, Stockholm (2011)
VINNOVA FFI project, VIRTUES (Virtualized Embedded Systems for Testing and Development). http://www.csc.kth.se/~karlm/virtues/
Whalen, M., Rajan, A, Heimdahl, M., Miller, S.: Coverage metrics for requirements-based testing. In: Proceedings of International Symposium on Software Testing and Analysis, ISSTA 2006, pp 25–35. ACM Press (2006)
Acknowledgement
K. Meinke wishes to thank VINNOVA and Scania AB for financial support of this research within [10], and R. Svenningson for valuable discussions on fault injection. P. Nycander wishes to thank TriOptima AB for hosting his Masters thesis research.
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Meinke, K., Nycander, P. (2015). Learning-Based Testing of Distributed Microservice Architectures: Correctness and Fault Injection. In: Bianculli, D., Calinescu, R., Rumpe, B. (eds) Software Engineering and Formal Methods. SEFM 2015. Lecture Notes in Computer Science(), vol 9509. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49224-6_1
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DOI: https://doi.org/10.1007/978-3-662-49224-6_1
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