A Systematic Mapping Study of Empirical Studies on Software Cloud Testing Methods

Al-Said Ahmad, A; Brereton, OP; Andras, PE

Abstract

Context: Software has become more complicated, dynamic, and asynchronous than ever, making testing more challenging. With the increasing interest in the development of cloud computing, and increasing demand for cloud-based services, it has become essential to systematically review the research in the area of software testing in the context of cloud environments. Objective: The purpose of this systematic mapping study is to provide an overview of the empirical research in the area of software cloud-based testing, in order to build a classification scheme. We investigate functional and non-functional testing methods, the application of these methods, and the purpose of testing using these methods. Method: We searched for electronically available papers in order to find relevant literature and to extract and analyze data about the methods used. Result: We identified 69 primary studies reported in 75 research papers published in academic journals, conferences, and edited books. Conclusion: We found that only a minority of the studies combine rigorous statistical analysis with quantitative results. The majority of the considered studies present early results, using a single experiment to evaluate their proposed solution.

Citation

Al-Said Ahmad, A., Brereton, O., & Andras, P. (2017). A Systematic Mapping Study of Empirical Studies on Software Cloud Testing Methods. In 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). https://doi.org/10.1109/QRS-C.2017.94

• Start Date: Jul 25, 2017
• End Date: Jul 29, 2017
• Acceptance Date: May 26, 2017
• Publication Date: Aug 18, 2017
• Series Title: International Workshop on Automation Testing of Cyber-Physical Systems in the Cloud (cpsATcloud)
• Book Title: 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)
• ISBN: 9781538620724
• DOI: https://doi.org/10.1109/QRS-C.2017.94