A hybrid novel fuzzy AHP-TOPSIS technique for selecting parameter-influencing testing in software development

Abstract

Software testing is one of the most important phases in the software development life cycle. Software testing cannot ensure successful outcomes until and unless done perfectly. For enhanced testing, it is extremely important to identify and prioritize the parameters that influence the testing process. Prioritization of Parameter-Influencing Testing (PIT) to ensure the testing environment’s reliability has piqued industry practitioners’ interest. A structured framework for the prioritization of PIT will result in the timely and successful execution of the software testing process. A case study for optimal PIT selection and ranking is conducted to address this problem by devising a hybrid technique based on a Fuzzy-Analytical Hierarchy Process (AHP) and Fuzzy-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In the proposed framework, the linguistic data obtained from the industry experts are represented as triangular fuzzy numbers used to quantify the expert’s uncertainty in the assessment of PITs with respect to selection criteria. Furthermore, the fuzzy set is integrated into the AHP to determine the selection criteria weights. Finally, a fuzzy TOPSIS is used for ranking PITs. The results reveal that ‘Automated Testing’, ‘Verification/Validation’and ‘Good Design Principles’ are the crucial PITs. The results of this study will aid industry experts in determining the applicability of PITs and demonstrating the efficacy of the proposed framework for the PITs evaluation and ranking.