BW-TOPSIS: A Hybrid Method to Evaluate Software Testing Techniques
Abstract
Software testing plays a significant role in various software development phases. There are so many software testing techniques available. Selecting the most suitable software testing technique based on multiple factors is challenging for software practitioners. This paper proposes an MCDM-based hybrid approach for selecting the most appropriate software testing technique among various available software testing techniques, considering multiple factors such as cost, schedule, resources, etc. Because of the involvement of multiple factors, the problem of selecting the most appropriate software testing technique can be modeled as an MCDM problem. This study proposes a hybrid approach by integrating two MCDM methods BWM (Best-Worst Method) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), for evaluating various software testing techniques considering multiple factors altogether. For the applicability of the proposed approach, an experimental study was conducted using seven software testing techniques and six evaluation criteria. Results show the proposed approach can be used as an efficient tool for selecting the most suitable software testing technique among various available testing techniques in the presence of multiple factors.
Keywords
Software Testing Technique, Multi-Criteria Decision Making, BWM, TOPSISThis work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
A. Kumar and K. Kaur, "BW-TOPSIS: A Hybrid Method to Evaluate Software Testing Techniques," in Journal of Communications Software and Systems, vol. 18, no. 4, pp. 336-342, December 2022, doi: https://doi.org/10.24138/jcomss-2022-0138
@article{kumar2022topsishybrid, author = {Ajay Kumar and Kamaldeep Kaur}, title = {BW-TOPSIS: A Hybrid Method to Evaluate Software Testing Techniques}, journal = {Journal of Communications Software and Systems}, month = {12}, year = {2022}, volume = {18}, number = {4}, pages = {336--342}, doi = {https://doi.org/10.24138/jcomss-2022-0138}, url = {https://doi.org/https://doi.org/10.24138/jcomss-2022-0138} }