A web-based software tool utilizing AI agents and prompt engineering to automate task prioritization and apply diverse prioritization techniques, aimed at enhancing project management within the agile framework is introduced.
Abstract
Large Language Models (LLMs) are revolutionizing Software Engineering (SE) by introducing innovative methods for tasks such as collecting requirements, designing software, generating code, and creating test cases, among others. This article focuses on requirements engineering, typically seen as the initial phase of software development that involves multiple system stakeholders. Despite its key role, the challenge of identifying requirements and satisfying all stakeholders within time and budget constraints remains significant. To address the challenges in requirements engineering, this study introduces a web-based software tool utilizing AI agents and prompt engineering to automate task prioritization and apply diverse prioritization techniques, aimed at enhancing project management within the agile framework. This approach seeks to transform the prioritization of agile requirements, tackling the substantial challenge of meeting stakeholder needs within set time and budget limits. Furthermore, the source code of our developed prototype is available on GitHub, allowing for further experimentation and prioritization of requirements, facilitating research and practical application.
This PhD dissertation studies how development teams create and use RE artifacts such as requirements and acceptance criteria, guided by the following main research question: How are Requirements Engineering artifacts used in Agile Software Development.
Algorithm-Driven Development is introduced, a methodology developed from industrial practice to address recurring challenges in translating requirements into reliable, testable, and maintainable software behavior that provides systematic coverage of functional scenarios from the outset of development.
Philippe Jawish, Pierre Evrard, Alexandre Lemerle et al.· Journal of Systems and Softw...· 0 citations
This research aims to identify and validate key challenges and their solutions within the RE process for open‐source software development (OSSD) and propose best practices to address these challenges.
Fazli Rabi, M. Ilyas, Nasir Rashid et al.· Journal of Software: Evoluti...· 0 citations
A lifecycle-aware framework that integrates quantitative software quality assessment with Large Language Model (LLM)-based code refinement is proposed and the potential of metric-driven LLM feedback for research software quality improvement is demonstrated while highlighting its inherently multi-objective nature.
Nafis Tanveer Islam, N. Soveizi, Yutong Li et al.· 0 citations
A hybrid prioritization framework that combines the hierarchical cumulative voting (HCV) with the best-worst method (BWM) is proposed, used to determine consistent expert weights with fewer pairwise comparisons for agile software development.
Salma A. Huwedi, Salwa M. Elakeili· Al-imad Journal of Humanitie...· 0 citations
Program Increment (PI) Planning is a critical synchronization event in scaled Agile methodologies, yet remains largely informal, with limited analytical rigor or strategic alignment. This paper introduces a formal metamodel and a model-driven framework to support structured PI Planning in large-scale software developme...
F. Somda, Désiré Guel, Kisito K. Kabore· Revue Africaine de Recherche...· 0 citations
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