Measurable & Scalable NFRs using Fuzzy Logic and Likert Scale

TL;DR

This paper introduces a hybrid approach combining fuzzy logic and Likert scales to measure and scale non-functional requirements, enhancing clarity and precision in NFR assessment.

Contribution

It proposes a novel integration of functional, measurable, and scalable NFRs using fuzzy logic and Likert scales, providing a new baseline for NFR frameworks.

Findings

Effective handling of discretely measurable NFRs

Successful scaling of NFRs like usability

Potential for baseline development in NFR frameworks

Abstract

Most of the research related to Non Functional Requirements (NFRs) have presented NFRs frameworks by integrating non functional requirements with functional requirements while we proposed that measurement of NFRs is possible e.g. cost and performance and NFR like usability can be scaled. Our novel hybrid approach integrates three things rather than two i.e. Functional Requirements (FRs), Measurable NFRs (M-NFRs) and Scalable NFRs (S-NFRs). We have also found the use of Fuzzy Logic and Likert Scale effective for handling of discretely measurable as well as scalable NFRs as these techniques can provide a simple way to arrive at a discrete or scalable NFR in contrast to vague, ambiguous, imprecise, noisy or missing NFR. Our approach can act as baseline for new NFR and aspect oriented frameworks by using all types of UML diagrams.