Test-Algebra Execution in a Cloud Environment

Abstract

A algebraic system, Test Algebra (TA), identifies faults in combinatorial testing for SaaS (Software-as-a-Service) applications. SaaS is a software delivery model that involves composition, deployment, and execution of mission application on cloud platforms. Testing SaaS applications is challenging because a large number of configurations needs to be tested. Faulty configurations should be identified and corrected before the delivery of SaaS applications. TA proposes an effective way to reuse existing test results to identify test results of candidate configurations. The TA also defines rules to permit results to be combined, and to identify the faulty interactions. Using the TA, configurations can be tested concurrently on different servers and in any order. This paper proposes one MapReduce design of TA concurrent execution in a cloud environment. The optimization of TA analysis is discussed. The proposed solutions are simulated using Hadoop in a cloud environment.

Test Algebra for Concurrent Combinatorial Testing

“…An interesting question is about the consistency of 1.6% as similar results were obtained using different parameters on smaller scale systems Tsai et al (2014);Wu et al (2014). This percentage does not go down or up significantly regardless of the experiment size.…”

“…An interesting scenario will happen when an X or F is identified, if there are few U configurations available, AR will not be effective as it needs a collection of configurations. One way to do this is to convert some N configurations into NU configuration, and run AR on U and NU configurations Wu et al (2014). In this case, it is possible that a configuration is evaluated before it has been selected.…”

“…NU configurations are from N configurations, but are treated as U configurations. Based on the existing F configurations, different algorithms such as Random, Hamming Distance, and mixed strategies can be used to get NU configurations from N configurations Wu et al (2014).…”

“…To evaluate the integrated process including its scalability, we performed extensive Kuhn et al (2008); Wu et al (2014), this may be the largest experimentation size in CT known to the authors as 2014.…”

A Geometric Dictionary Learning Based Approach for Fluorescence Spectroscopy Image Fusion

“…Following the development of cloud computing, cloud environment provides more and more strong computation capacity to process various images [1][2][3]. Due to the limited depth-of-focus of optical lenses in imaging sensors, one-time focus cannot guarantee to obtain all focused image in the whole scene [4].…”