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PHandler: An expert system for a scalable software requirements prioritization process

Babar, Muhammad Imran and Ghazali, Masitah and Jawawi, Dayang Norhayati Abang and Shamsuddin, Siti Mariyam and Ibrahim, Noraini (2015) PHandler: An expert system for a scalable software requirements prioritization process. Knowledge-Based Systems, 84 . pp. 179-202. ISSN 0950-7051

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Official URL: http://dx.doi.org/10.1016/j.knosys.2015.04.010

Abstract

Software requirements engineering is a critical discipline in the software development life cycle. The major problem in software development is the selection and prioritization of the requirements in order to develop a system of high quality. This research analyzes the issues associated with existing software requirement prioritization techniques. One of the major issues in software requirement prioritization is that the existing techniques handle only toy projects or software projects with very few requirements. The current techniques are not suitable for the prioritization of a large number of requirements in projects where requirements may grow to the hundreds or even thousands. The research paper proposes an expert system, called the Priority Handler (PHandler), for requirement prioritization. PHandler is based on the value-based intelligent requirement prioritization technique, neural network and analytical hierarchical process in order to make the requirement prioritization process scalable. The back-propagation neural network is used to predict the value of a requirement in order to reduce the extent of expert biases and make the PHandler efficient. Moreover, the analytical hierarchy process is applied on prioritized groups of requirements in order to enhance the scalability of the requirement prioritization process.

Item Type:Article
Uncontrolled Keywords:artificial neural networks, decision support, expert systems, hybrid model, software requirement prioritization
Subjects:A General Works
ID Code:58817
Deposited By: Haliza Zainal
Deposited On:04 Dec 2016 12:07
Last Modified:02 Mar 2017 11:03

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