Monte Carlo Simulation for Risk Management in ِِِAgile Software Development

Abstract

Agile development methodologies are becoming increasingly popular in agile development projects due to their iterative nature and adaptability. The Monte Carlo method is distinguished by its statistical technique of using random samples to obtain many satisfactory results for solving uncertainty. It can be used in agile software development by building different scenarios and measuring their impact on the project results through statistical operations. Its ability to meet significant challenges in managing risk and uncertainty mitigation. In this study, we propose a Monte Carlo simulation-based approach to measure and analyze risks in the agile development process. It provides a probabilistic framework for risk assessment by integrating the Monte Carlo simulation methodology to model the various development process variables. It was addressed by identifying the main risk factors within agile projects, such as tasks, availability of resources, and external dependencies. The proposed approach contributes to mitigating potential risks in agile software development using Monte Carlo theory, which provides a systematic framework that enables work teams and management to overcome risk and uncertainty associated with the agile development process in dynamic project environments.