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Abstract
Software requirements prioritization and selection is an important activity of the requirements elicitation process. The objective of this process is to prioritize the software requirements so that high-ranked requirements can be selected for implementation. The information stored in the fuzzy-based methods contains vague or uncertain statements of stakeholder’s perceptions. This is modeled by the different types of membership functions. In these methods, selection of the membership function depends on the subjective judgements and thus it lacks objectivity. As a result, it may change the ranking values of the software requirements. To address this issue, this paper presents a method for the prioritization and selection of the software requirements using rough-set theory. The proposed method is compared with three fuzzy-based methods which are used to calculate the ranking values of software requirements. Both small and large set of requirements of an examination system have been used in comparative study based on the following criteria: (a) agreement measure, (b) number of judgements by decision makers, and (c) modeling of uncertainty.
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No potential conflict of interest was reported by the author(s).
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Notes on contributors
Mohd Sadiq
Mohd Sadiq is working as a post-doctoral fellow at the Department of Computer Science and Automation, Indian Institute of Science (IISc) Bangalore, India. He is on study leave from Jamia Millia Islamia (JMI), a Central University, New Delhi, India, for his post-doctoral research at IISc Bangalore, India. In 2017, he received PhD degree in computer engineering from the National Institute of Technology, Kurukshetra, India. Prior to joining IISc Bangalore, he has worked as post-doctoral fellow at the Center for Soft Computing Research, Indian Statistical Institute (ISI), Kolkata, India; and also, as a visiting scientist at the Systems Science and Informatics Unit, ISI, Bangalore Centre, India. He received MTech degree in computer science and engineering from Aligarh Muslim University, Aligarh, India, in 2005. He has delivered expert lectures on artificial intelligence at the Indian Institute of Information Technology Lucknow, India. Dr Sadiq published his research work in the following reputed journals: Business & Information Systems Engineering, Taylor and Francis; IETE Journal of Research, Taylor and Francis; International Journal of Information Technology, Springer; International Journal of System Assurance Engineering and Management, Springer; International Journal of Computers and Applications, Taylor and Francis; CSI Transactions on ICT, Springer; International Journal of Business Information Systems, Inderscience, and Conferences like RePrico@RE-2014, Sweden, SEKE-2013, USA, etc. His research interests lie at the intersection of software engineering and fuzzy/rough set based multicriteria decision-making algorithms.
V. Susheela Devi
V Susheela Devi is working as a principal research scientist at the Department of Computer Science and Automation, Indian Institute of Science (IISc) Bangalore, India. She received PhD degree from IISc Bangalore in 2000. She has supervised more than 30 MTech dissertations in the area of artificial intelligence and image processing. Dr Devi is currently supervising two PhD students in the area of artificial intelligence and machine learning and one postdoc student in the area of soft computing. She has published her research work in reputed journals like IEEE Transactions on Power Delivery; Pattern Recognitions, ScienceDirect, International Journal of Information Technology, Springer; Sadhana, Journal of the Indian Academy of Sciences, Journal of Artificial Intelligence and Soft Computing Research, etc.; and conferences like ACM CODS-COMAD-2020, ICONIP-2019/2018, etc. Her research interest includes pattern analysis, machine intelligence, and soft computing. Email: [email protected]