A Survey on Cloud Adoption for Software Testing: Integrating Empirical Data with Fuzzy Multicriteria Decision-Making

Abstract

With the introduction of cloud computing, the field of software development and testing has experienced substantial changes. The effectiveness and scalability of traditional software testing techniques are challenged by the distributed and more complex nature of contemporary applications. Testing-as-a-Service (TaaS) or Cloud-Based Testing (CBT) is a promising option made possible by cloud computing's scalable on-demand capabilities. CBT has drawbacks in terms of security, privacy, and service quality even with its possible advantages, such as increased productivity and cost-effectiveness. The objective of this research is to close the gap by creating a thorough Cloud Testing Adoption Assessment Model (CTAAM) with the use of fuzzy multicriteria decision-making (FMCDM) techniques and empirical data. The model uses empirical data and expert views to examine and assess the factors impacting cloud adoption in software testing, ultimately aiding decision-making in software development organizations (SDOs).