The method of requirements prioritization in software engineering
Abstract
In software development processes, requirements prioritization plays a key role. Proper gathering of requirements and their objective prioritization can ensure a sequential and effective development of a software project. With the increasing complexity of software, which is a characteristic of today, problems related to defining requirements also increase. It becomes increasingly challenging to identify the most important and essential requirements in a stream of wishes and recommendations, determining what should be the starting point of development and where the most attention should be focused. The task of requirements prioritization is multi-criterial and poses significant cognitive loads. Most researchers and professionals suggest expert methods for decision-making in such environments, which to some extent help solve the tasks at hand. However, among the known requirements prioritization methods, practically all involve qualitative descriptive analysis based on brainstorming techniques. At the same time, in the modern conditions of digitalization, providing decision support based on a comprehensive presentation of the information model of the subject area and processing through information technologies for quantitative assessment of alternatives is more promising. Another important capability of modern technologies is visualization of decision-making processes. Thus, this work explores a comprehensive prioritization method that involves a full presentation of the information picture of the subject area, including in the form of computer ontologies, applying a quantitative AHP method for comparing requirements, and visualized data in gra phs for considering alternatives. Additional use of a modified SWOT matrix allows for the disaggregation of requirements into their individual characteristics and consideration of their advantages for problem evaluation. The existence of such tools and the capabilities of information technologies confirm the effectiveness and stability of the proposed method.
Problems in programming 2024; 2-3: 132-139
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