RiskControl: A Bayesian Network-based Tool to Support Risk Management in Software Projects

Researchers have investigated several software project risk management approaches and developed promising techniques and tools for identifying, measuring, and monitoring risks. Among these techniques, Bayesian Networks (BNs) provide quick responses when variables change. However, using these tools requires solid knowledge of BNs because they rely on different platforms, such as AgenaRisk and NETICA, to create probabilistic models. This paper presents RiskControl, a BN-based tool that helps practitioners manage risks. RiskControl simplifies Bayesian theory concepts for the end user, improving the tool’s usability. It also provides mechanisms for identifying risks based on a project’s technical constraints, measuring them, recommending contingency plans, and monitoring these events. Preliminary tests of RiskControl in the industry have produced satisfactory results. We provide examples of its use and evidence that our proposed tool can support practitioners’ decision-making in risk management.