A Fuzzy AHP-based Quantitative Framework to Prioritize the Crowd-Based Requirements

Softwarerequirement plays a vital role in the success of a software project. However, the quality of requirement management remains a key challenge for a project manager, especially in a Crowdsourcing context. In Crowdsourcing, the customers belong from diverse locations; thereby, providing the redundant and inconsistent requirements for a targeted software system. To the best of our knowledge, the existing literature lacks in providing a quantitative framework that prioritizes the crucial factors affecting the requirement's management in the Crowdsourcing context. Motivated by this, we propose a quantitative framework that will be effective in ranking the Crowdsourcing-based requirements. For this purpose, the current study intends to identify various factors, that can affect the management of requirements, from the literature and also validates them from the practitioners. To accomplish this, we perform a systematic review and an empirical study. Moreover, we quantify the impact of each factor using the capability of a multi-criteria decision-making oriented Fuzzy- Analytical Hierarchy Process (F-AHP) technique. Subsequently, we also employ a multi-perspective prioritization technique to obtain the data from the relevant personnel to validate the quantified score. To assess the performance of the proposed quantitative framework, we considered a real-world Smart Home case study. Moreover, the efficacy of the adopted F-AHP technique is validated by comparing it with the traditional AHP technique. The results indicate that the F-AHP technique significantly outperformed the baseline technique.