Strategies for Early Identification of Failures in Agile Software Development Projects – A Review - Nanwin, Domaka Nuka; Agaji, Iorshase; Ogala, Emmanuel; Gbaden, Terlumum (Faculty of Natural and Applied Sciences Journal of Computing and Applications, 2025)
Agile software development has gained widespread adoption due to its iterative and adaptive approach to project management. However, despite its benefits, Agile projects are susceptible to failures that can impede project success. This paper focuses on developing effective strategies for early identifying and preventing of these failures in Agile software development projects. The aim is to provide project teams and stakeholders with actionable insights to mitigate failures and enhance project outcomes. The methodology involves a comprehensive review of literatures on Agile project management, early failure detection, and classification analysis using a novel failure detection analysis (FDA) model/ framework. Expected results include the formulation of a practical framework comprising proactive measures and best practices for early detection and prevention of software project failures. Suggestions for implementation include implementing refined machine learning algorithms, exploring performance metrics, conducting longitudinal studies, and empirical studies in diverse contexts while leveraging Agile project management tools for continuous monitoring and adaptation. In conclusion, by implementing the proposed strategies, Agile software development teams can proactively identify and mitigate potential failures, leading to improved software project success rates and stakeholder satisfaction.