1 Business Full Spectrum, United Kingdom.
2 System/information Analyst, Greenville Texas, USA.
3 Tranter IT Infrastructure Services Limited, Nigeria.
4 Independent Researcher, United Kingdom.
Review Article
World Journal of Advanced Research and Reviews, 2024, 22(01), 1209-1220
Received on 11 March 2024; revised on 20 April 2024; accepted on 22 April 2024
Requirements elicitation is a crucial phase in the software development lifecycle, ensuring that stakeholders' needs are understood and translated into system specifications. Traditional methods often face challenges such as ambiguity, inconsistency, and evolving requirements, leading to project delays and cost overruns. This review proposes a conceptual model that integrates advancements and innovations in requirements elicitation to address these challenges comprehensively. The proposed model leverages various techniques, including but not limited to, natural language processing (NLP), machine learning (ML), and human-computer interaction (HCI), to enhance the accuracy and efficiency of requirements elicitation. NLP techniques enable automated analysis of textual requirements documents, extracting key information and identifying implicit requirements. ML algorithms facilitate the prediction of potential changes in requirements based on historical data and project context, enabling proactive management of evolving requirements. Moreover, the integration of HCI principles in the requirements elicitation process enhances stakeholder engagement and collaboration. Interactive interfaces and visualization tools enable stakeholders to provide feedback in real-time, fostering a more iterative and participatory approach to requirement gathering. Additionally, techniques such as prototyping and simulation facilitate early validation of requirements, reducing the risk of misinterpretation and ensuring alignment with stakeholders' expectations. Furthermore, the proposed model emphasizes the importance of context-awareness in requirements elicitation. By considering the organizational, cultural, and environmental context of a project, the model adapts its elicitation strategies and techniques to suit specific needs and constraints. Context-awareness also enables the identification of implicit requirements that may not be explicitly stated but are crucial for the success of the system. The model also addresses the challenge of managing conflicting requirements by introducing a systematic approach to requirements prioritization and negotiation. By employing multi-criteria decision-making techniques, stakeholders can collaboratively prioritize requirements based on their importance, feasibility, and impact on project objectives. Conflict resolution mechanisms facilitate consensus-building and trade-off analysis, ensuring that the final set of requirements reflects the collective interests of all stakeholders. Additionally, the proposed model emphasizes the iterative nature of requirements elicitation, advocating for continuous refinement and validation of requirements throughout the development lifecycle. Feedback loops enable stakeholders to review and revise requirements based on evolving needs and changing circumstances, thereby enhancing the adaptability and resilience of the system. The conceptual model presented in this review represents a holistic approach to requirements elicitation, leveraging advancements and innovations in technology, human interaction, and context-awareness. By integrating these elements, the model aims to enhance the accuracy, efficiency, and stakeholder satisfaction in the requirements elicitation process, ultimately contributing to the successful delivery of high-quality software systems.
Advancement; Innovation; Requirement elicitation; Comprehensive conceptual model
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Oladapo Adeboye Popoola, Henry Ejiga Adama, Chukwuekem David Okeke and Abiodun Emmanuel Akinoso. Advancements and innovations in requirements elicitation: Developing a comprehensive conceptual model. World Journal of Advanced Research and Reviews, 2024, 22(1), 1209-1220. Article DOI: https://doi.org/10.30574/wjarr.2024.22.1.1202