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 redu...

Full description

Saved in:
Bibliographic Details
Main Authors: Rehman Khan, Saif Ur, Younus, Maha, Iqbal, Javed, Basit Ur Rahim, Muhammad Abdul
Format: Conference Proceeding
Language:English
Subjects:
Analytic hierarchy process
crowd-based requirements engineering
Crowdsourcing
empirical study
fuzzy AHP
multi-criteria decision-making
Personnel
quantitative framework
Reliability engineering
Requirements management
Security
Smart homes
Software quality
Software reliability
Software systems
systematic review
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2693-9371
DOI:10.1109/QRS-C63300.2024.00090