Abstract
This chapter discusses combinatorial testing in multi-tenancy Software-as-a-Service (SaaS) system. SaaS often uses multi-tenancy architecture (MTA) where tenant developers compose their applications online using the components stored in the SaaS database. Tenant applications need to be tested, and combinatorial testing can be used. While numerous combinatorial testing techniques are available, most of them produce static sequence of test configurations and their goal is often to provide sufficient coverage such as 2-way interaction coverage. But the goal of SaaS testing is to identify those compositions that are faulty for tenant applications. In this chapter, it proposes an adaptive test configuration generation algorithm called adaptive reasoning (AR) that can rapidly identify those faulty combinations so that those faulty combinations cannot be selected by tenant developers for composition. Whenever a new component is submitted to the SaaS database, the AR algorithm can be applied so that any faulty interactions with new components can be identified to continue to support future tenant applications.
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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) (IEEE, 2015), pp. 169–178
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 Fault Detection In Multi-tenancy Saas Systems. In: Combinatorial Testing in Cloud Computing. SpringerBriefs in Computer Science. Springer, Singapore. https://doi.org/10.1007/978-981-10-4481-6_3
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DOI: https://doi.org/10.1007/978-981-10-4481-6_3
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Publisher Name: Springer, Singapore
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Online ISBN: 978-981-10-4481-6
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