Moving software testing to the cloud: an adoption assessment model based on fuzzy multi-attribute decision making algorithm

Software testing is a challenge for several software development companies, particularly for companies involved in large-scale projects. To cope with these challenges employing Cloud computing (CC) technology would be the best choice. Testing-as-a-service (TaaS) is a pay-for-use model of testing for cloud-based applications, SaaS, and clouds itself that provide internet-based testing services for software development organization (SDO). However, moving testing to the CC environment is not free of cost, nor it is the best possible solution for all testing problems. Moreover, recent studies confirm lack of a comprehensive model for assessing the suitability of CC for software testing. To guide SDO on the adoption of CC for software testing, the proposed study aims at developing a cloud testing adoption assessment model, an application of multi-attribute decision-making method, based on the codified knowledge of field expert. The proposed model will provide decision support to SDO in the form of various predictors and determinants that will guide SDO towards CC adoption.