Performance analysis of Pythagorean fuzzy entropy and distance measures in selecting software reliability growth models using TOPSIS framework

Abstract

Purpose

The purpose of this paper is to create a numerical technique to tackle the challenge of selecting software reliability growth models (SRGMs).

Design/methodology/approach

A real-time case study with five SRGMs tested against a set of four selection indexes were utilised to show the functionality of TOPSIS approach. As a result of the current research, rating of the different SRGMs is generated based on their comparative closeness.

Findings

An innovative approach has been developed to generate the current SRGMs selection under TOPSIS environment by blending the entropy technique and the distance-based approach.

Originality/value

In any multi-criteria decision-making process, ambiguity is a crucial issue. To deal with the uncertain environment of decision-making, various devices and methodologies have been explained. Pythagorean fuzzy sets (PFSs) are perhaps the most contemporary device for dealing with ambiguity. This article addresses novel tangent distance-entropy measures under PFSs. Additionally, numerical illustration is utilized to ascertain the strength and authenticity of the suggested measures.

Citation

Arora, H.D. and Naithani, A. (2023), "Performance analysis of Pythagorean fuzzy entropy and distance measures in selecting software reliability growth models using TOPSIS framework", International Journal of Quality & Reliability Management, Vol. 40 No. 7, pp. 1667-1682. https://doi.org/10.1108/IJQRM-11-2021-0398