Evaluating Agile Methodologies for Software Requirements and Construction: A SWEBOK-Based Analysis

Agile methodologies have gained widespread adoption in software development due to their flexibility, iterative approach, and focus on collaboration. However, their effectiveness in addressing critical software engineering domains, particularly the Software Requirements and Software Construction Knowledge Areas (KAs), remains an open question. This study systematically evaluates five agile methodologies—Extreme Programming (XP), Scrum, Feature-Driven Development (FDD), Rapid Application Development (RAD), and Kanban—using a comparative framework built upon key attributes from the Software Engineering Body of Knowledge (SWEBOK). The assessment considers how each methodology approaches requirements gathering, change management, software design, coding practices, and overall project adaptability. By analyzing these methodologies through the lens of SWEBOK Knowledge Areas, this research aims to identify their strengths, limitations, and applicability to different types of software projects. The findings provide valuable insights for software practitioners, project managers, and educators in selecting the most appropriate agile methodology based on project complexity, team structure, and development constraints. Additionally, this study highlights potential gaps in agile methodologies concerning software engineering best practices, paving the way for future research and methodological enhancements. Ultimately, this research contributes to a deeper understanding of how agile practices align with formal software engineering principles, aiding organizations in making more informed decisions when adopting agile frameworks.

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Publication Details

Journal
Transactions on Machine Learning and Artificial Intelligence
Published
2025-04-25
DOI
https://doi.org/10.14738/tmlai.1302.18659
Primary Topic
Software Engineering Techniques and Practices
Type
article
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article

Evaluating Agile Methodologies for Software Requirements and Construction: A SWEBOK-Based Analysis

Bouchaib Falah
Transactions on Machine Learning and Artificial Intelligence
Software Engineering Techniques and Practices
article

Evaluating Agile Methodologies for Software Requirements and Construction: A SWEBOK-Based Analysis

Bouchaib Falah
article en

Abstract

Agile methodologies have gained widespread adoption in software development due to their flexibility, iterative approach, and focus on collaboration. However, their effectiveness in addressing critical software engineering domains, particularly the Software Requirements and Software Construction Knowledge Areas (KAs), remains an open question. This study systematically evaluates five agile methodologies—Extreme Programming (XP), Scrum, Feature-Driven Development (FDD), Rapid Application Development (RAD), and Kanban—using a comparative framework built upon key attributes from the Software Engineering Body of Knowledge (SWEBOK). The assessment considers how each methodology approaches requirements gathering, change management, software design, coding practices, and overall project adaptability. By analyzing these methodologies through the lens of SWEBOK Knowledge Areas, this research aims to identify their strengths, limitations, and applicability to different types of software projects. The findings provide valuable insights for software practitioners, project managers, and educators in selecting the most appropriate agile methodology based on project complexity, team structure, and development constraints. Additionally, this study highlights potential gaps in agile methodologies concerning software engineering best practices, paving the way for future research and methodological enhancements. Ultimately, this research contributes to a deeper understanding of how agile practices align with formal software engineering principles, aiding organizations in making more informed decisions when adopting agile frameworks.

Transactions on Machine Learning and Artificial IntelligenceVol. 13(02)
Lincoln University - Pennsylvania (US)
Openalex Percentile: Top 82%
Software Engineering Techniques and Practices
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