Adaptive fault detection for testing tenant applications in multi-tenancy SaaS systems

W. T. Tsai, Qingyang Li, Charles Colbourn, Xiaoying Bai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

SaaS (Software-as-a-Service) 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 sequences 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. This paper proposes an adaptive test configuration generation algorithm AR (Adaptive Reasoning) that can rapidly identify those faulty combinations so that those faulty combinations cannot be selected by tenant developers for composition. The AR 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 showed show that the AR algorithm can identify those faulty combinations rapidly. 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.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE International Conference on Cloud Engineering, IC2E 2013
Pages183-192
Number of pages10
DOIs
StatePublished - 2013
Event1st IEEE International Conference on Cloud Engineering, IC2E 2013 - San Francisco, CA, United States
Duration: Mar 25 2013Mar 28 2013

Other

Other1st IEEE International Conference on Cloud Engineering, IC2E 2013
CountryUnited States
CitySan Francisco, CA
Period3/25/133/28/13

Fingerprint

Fault detection
Testing
Adaptive algorithms
Chemical analysis
Application programs
Engines
Experiments

Keywords

  • Adpative testing
  • Combinatorial testing
  • SaaS (Software-as-a-Service)
  • Testing tenant applications

ASJC Scopus subject areas

  • Software

Cite this

Tsai, W. T., Li, Q., Colbourn, C., & Bai, X. (2013). Adaptive fault detection for testing tenant applications in multi-tenancy SaaS systems. In Proceedings of the IEEE International Conference on Cloud Engineering, IC2E 2013 (pp. 183-192). [6529283] https://doi.org/10.1109/IC2E.2013.44

Adaptive fault detection for testing tenant applications in multi-tenancy SaaS systems. / Tsai, W. T.; Li, Qingyang; Colbourn, Charles; Bai, Xiaoying.

Proceedings of the IEEE International Conference on Cloud Engineering, IC2E 2013. 2013. p. 183-192 6529283.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Tsai, WT, Li, Q, Colbourn, C & Bai, X 2013, Adaptive fault detection for testing tenant applications in multi-tenancy SaaS systems. in Proceedings of the IEEE International Conference on Cloud Engineering, IC2E 2013., 6529283, pp. 183-192, 1st IEEE International Conference on Cloud Engineering, IC2E 2013, San Francisco, CA, United States, 3/25/13. https://doi.org/10.1109/IC2E.2013.44
Tsai WT, Li Q, Colbourn C, Bai X. Adaptive fault detection for testing tenant applications in multi-tenancy SaaS systems. In Proceedings of the IEEE International Conference on Cloud Engineering, IC2E 2013. 2013. p. 183-192. 6529283 https://doi.org/10.1109/IC2E.2013.44
Tsai, W. T. ; Li, Qingyang ; Colbourn, Charles ; Bai, Xiaoying. / Adaptive fault detection for testing tenant applications in multi-tenancy SaaS systems. Proceedings of the IEEE International Conference on Cloud Engineering, IC2E 2013. 2013. pp. 183-192
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