A multi-criteria decision-making approach for optimal selection of software reliability growth models. (3rd June 2022) - Gupta, Aakash; Garg, Rakesh
The software industries are major stakeholders in the economy of any country. Most business processes are now implemented through software both online and off-line. Before this software is deployed and delivered to the client, it is essential for the solution provider to extensively check its reliability. Reliability is an important factor that directly affects the future of any software in the market. The reliability of software could be enhanced by the use of Software Reliability Growth Models (SRGMs). In the present research, a hybrid Multi-Criteria Decision Making (MCDM) approach, namely Entropy-Evaluation based on Distance from Average Solution (EEDAS) is proposed and implemented to rank the sixteen SRGMs by selecting nine criteria using a failure data set. Further, the EEDAS method results are compared with well-known methods WEDBA and TOPSIS and validated by Kendall's tau correlation test. The present research results based on EDAS show that the Pham Zhang IFD model is the best one whereas the Gompert model is the worst.