Requirement Prioritization in Software Engineering: a Systematic Literature Review Update

Renato Cesar Ais; Érica Ferreira De Souza; Alinne C. Correa Souza

doi:10.5753/jis.2026.5371

Authors

Renato Cesar Ais Federal University of Technology of Paraná https://orcid.org/0009-0009-4175-6481
Érica Ferreira De Souza Federal University of Technology of Paraná https://orcid.org/0000-0001-7262-7863
Alinne C. Correa Souza Federal University of Technology of Paraná https://orcid.org/0000-0002-2525-7801

DOI:

https://doi.org/10.5753/jis.2026.5371

Keywords:

Requirement Engineering, Requirements Prioritization, Systematic Literature Review, Updated

Abstract

Context: Software requirements prioritization is the classification and ordering of requirements given their priority. This ordering can be done using prioritization techniques. Knowing the main prioritization techniques is essential for advancing research in Requirement Engineering. A Systematic Literature Review (SLR) published in 2021 presented evidence on requirements prioritization techniques, their limitations, a list of identified techniques, and the criteria used in
the prioritization process. An assessment of this SLR revealed the need for an update. Purpose: This study aims to update the previous SLR and contribute to the current state of research on this topic. Method: First, we conducted a tertiary study to identify other reviews addressing the same topic. Then, we applied the 3PDF framework to evaluate the feasibility of SLR updating, and finally, we updated the previous SLR. In this update, we consider new research questions and analyses of the extracted data. This update incorporates new research questions and additional analyses of the extracted data. Results: The updated SLR identified a total of 45 relevant studies between 2021 and June 2025, shedding new light on the evolution of requirements prioritization. We identified 32 distinct requirements prioritization techniques, with 23 of these being novel, adding a fresh perspective to the area. Conclusion: This updated SLR provides a comprehensive view of the continuous evolution in requirements prioritization. The review highlights significant advancements in the use of Machine Learning (ML) and Artificial Intelligence (AI) techniques, alongside the enduring popularity of traditional methods such as the Analytic Hierarchy Process (AHP) and MoSCoW. Understanding these trends is crucial for practitioners, as they reflect persistent challenges in decision-making, including the influence of individual preferences and domain knowledge on the prioritization process.

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