SRPTackle: a semi-automated requirements prioritisation technique for scalable requirements of software system projects

Fadhl, Hujainah and Rohani, Abu Bakar and Nasser, Abdullah B. and Al-haimi, Basheer and Kamal Z., Zamli (2021) SRPTackle: a semi-automated requirements prioritisation technique for scalable requirements of software system projects. Information and Software Technology, 131 (106501). pp. 1-15. ISSN 0950-5849. (Published)

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Context: Requirement prioritisation (RP) is often used to select the most important system requirements as perceived by system stakeholders. RP plays a vital role in ensuring the development of a quality system with defined constraints. However, a closer look at existing RP techniques reveals that these techniques suffer from some key challenges, such as scalability, lack of quantification, insufficient prioritisation of participating stakeholders, overreliance on the participation of professional expertise, lack of automation and excessive time consumption. These key challenges serve as the motivation for the present research. Objective: This study aims to propose a new semiautomated scalable prioritisation technique called ‘SRPTackle’ to address the key challenges. Method: SRPTackle provides a semiautomated process based on a combination of a constructed requirement priority value formulation function using a multi-criteria decision-making method (i.e. weighted sum model), clustering algorithms (K-means and K-means++) and a binary search tree to minimise the need for expert involvement and increase efficiency. The effectiveness of SRPTackle is assessed by conducting seven experiments using a benchmark dataset from a large actual software project. Results: Experiment results reveal that SRPTackle can obtain 93.0% and 94.65% as minimum and maximum accuracy percentages, respectively. These values are better than those of alternative techniques. The findings also demonstrate the capability of SRPTackle to prioritise large-scale requirements with reduced time consumption and its effectiveness in addressing the key challenges in comparison with other techniques. Conclusion: With the time effectiveness, ability to scale well with numerous requirements, automation and clear implementation guidelines of SRPTackle, project managers can perform RP for large-scale requirements in a proper manner, without necessitating an extensive amount of effort (e.g. tedious manual processes, need for the involvement of experts and time workload).

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Binary trees; Decision making; K-means clustering; Large dataset
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Institute of Postgraduate Studies
Faculty of Computing
Depositing User: Mrs Norsaini Abdul Samat
Date Deposited: 28 Jul 2021 08:52
Last Modified: 28 Jul 2021 08:52
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