The expansion of the online food delivery apps (OFDAs) around the globe has accelerated because of the sudden growing cases of the COVID-19 pandemic. OFDAs are quickly expanding in India, providing a huge number of chances for different OFDA platforms and creating a competitive market. There are several criteria and dimensions for OFDAs businesses to explore to keep with the frequently changing competitive market and achieve long-term success. A Pythagorean fuzzy set (PFS) is a powerful tool for dealing with uncertainty. Distance measure of PFS is a hot research topic and has real-life applications in many areas, such as decision making, medical diagnosis, patterns analysis, clustering, etc. The article aims to examine the results of the novel Pythagorean fuzzy distance measure strategy to select the best online app using TOPSIS method to select the best OFDAs. Firstly, all the axioms related to distance measures are proved for the proposed measures. The proposed work uses five distinct alternatives/options and four attributes/criteria in a fuzzy environment to deal with imprecise and conflicting information. The findings indicate that the proposed methodology is a more realistic way to choose the best OFDAs among others. Finally, a sensitivity analysis is used to determine whether the chosen alternative was the best option among the other components and to ensure that the TOPSIS technique results were accurate.

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.

Information theory concept was created by Claude Shannon in 1948. Entropy i.e. uncertainty measure informs how much information is there in an event. The more uncertain the event the more information it gives. In order to resolve this uncertainty, software testing is done and by running it, knowledge of a software system is gained. In this paper, a benchmark for modeling of bug prediction using different measures of entropy mainly Shannon, Renyi and Tsallis entropy have been presented. Information theory is also needed to enable the communication system to carry information from sender to receiver over a communication channel.