Environmental Modeling for Automated Cloud Application Testing

Zhang, Linghao; Ma, Xiaoxing; Lu, Jian; Xie, Tao; Tillmann, Nikolai; de Halleux, Peli
March 2012
IEEE Software;Mar2012, Vol. 29 Issue 2, p30
Academic Journal
Platforms such as Windows Azure let applications conduct data-intensive cloud computing. Unit testing can help ensure high-quality development of such applications, but the results depend on test inputs and the cloud environment's state. Manually providing various test inputs and cloud states is laborious and time-consuming. However, automated test generation must simulate various cloud states to achieve effective testing. To address this challenge, a proposed approach models the cloud environment and applies dynamic symbolic execution to generate test inputs and cloud states. Applying this approach to open-source Azure cloud applications shows that it can achieve high structural coverage.


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