Abstract
A new integrated testing framework is proposed to use adaptive reasoning algorithm with automated test cases generation (ARP) and test algebra (TA) for increasing SaaS testing efficiency in faulty combination identification and elimination. The ARP algorithm has been evaluated by both simulation and real experimentation using a MTA SaaS sample running on GAE (Google App Engine). Both the simulation and experiment show that the ARP algorithm can identify those faulty combinations rapidly and TA can eliminate a large number of faults from candidate test set with a small number of seeded faults.
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References
W.-T. Tsai, G. Qi, Integrated adaptive reasoning testing framework with automated fault detection, in Proceedings of IEEE Symposium on Service-Oriented System Engineering (SOSE2015), pp. 169–178. IEEE, 2015
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W.-T. Tsai, Q. Li, C.J. Colbourn, X. Bai, Adaptive fault detection for testing tenant applications in multi-tenancy SaaS systems, in Proceedings of IEEE International Conference on Cloud Engineering (IC2E), 2013
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Tsai, WT., Qi, G. (2017). Adaptive Reasoning Algorithm with Automated Test Cases Generation and Test Algebra in Saas System. In: Combinatorial Testing in Cloud Computing. SpringerBriefs in Computer Science. Springer, Singapore. https://doi.org/10.1007/978-981-10-4481-6_7
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DOI: https://doi.org/10.1007/978-981-10-4481-6_7
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Publisher Name: Springer, Singapore
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Online ISBN: 978-981-10-4481-6
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