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Implementing weighted entropy-distance based approach for the selection of software reliability growth models

A computational quantitative model based on Weighted Euclidean Distance Based Approximation (WEBDA) has been developed to evaluate selection and rank the Software Reliability Growth Models (SRGMs) in ascending or descending order based on their Euclidean distance value from the optimal SRGM. The SRGM with Rank 1 is considered the optimal selection for the software developers on the particular dataset under consideration. The main problem of SRGMs selection and ranking is deployed as a multi-criteria decision making (MCDM) problem in which numerous inter-related attributes collectively termed as ranking criteria are identified to make the evaluation of available alternatives. In the present research, a data set from Tandem Computer Software Failure has been used to show the utility of developed model. Further the concept of methodology validation strengthens the present research by doing the comparison of obtained results with that of existing MCDM approaches such as Analytical Hierarchy Processing (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).