This paper conducts a comparative analysis of three widely adopted Agile methodologies: Scrum, Kanban, and Extreme Programming (XP). By examining their application across diverse software development environments, the study highlights each methodology's inherent strengths and explores their practical implications for managing complex, large-scale projects. Central to this investigation are the scalability challenges that become particularly pronounced in settings with extensive stakeholder groups and complex coordination needs. The research draws upon a robust literature review and case studies to identify these challenges, setting the stage for a discussion of innovative solutions aimed at refining Agile practices. While specific solutions are reserved for detailed treatment in the proposed solutions section, the abstract is written to underscore the critical need for scalable strategies that can adapt to the dynamic landscapes of modern project management. This comparative inquiry not only enriches the academic discourse on Agile methodologies but also serves as a vital resource for practitioners seeking to optimize their project management strategies in complex scenarios.

Change, in software requirements during its development phases, is considered as a major risk which may affect a software project to fail. Therefore, software engineering processes, methods, and tools are used in order to manage these risks whereas changes in requirements have many negative influences such as effects on system development life cycle (SDLC) phases, project progress, and outcome of a software project. Consequently, project managers must use risk management strategies, activities, and estimation techniques in order to manage and mitigate these risks which are caused due to changes in requirements. A novel model is proposed in this paper to manage and mitigate risks related to changing requirements. The proposed model is validated through qualitative research design. The results are in favor of the proposed model to show its effectiveness. It is anticipated that the proposed model will solve the problems of software companies in major to deal with risks about changing requirements.