Supporting early decision-making in the presence of uncertainty

Abstract

Requirements Engineering (RE) involves eliciting, understanding, and capturing system requirements, which naturally involves much uncertainty. During RE, analysts choose among alternative requirements, gradually narrowing down the system scope, and it is unlikely that all requirements uncertainties can be resolved before such decisions are made. There is a need for methods to support early requirements decision-making in the presence of uncertainty. We address this need by describing a novel technique for early decision-making and tradeoff analysis using goal models with uncertainty. The technique analyzes goal satisfaction over sets of models that can result from resolving uncertainty. Users make choices over possible analysis results, allowing our tool to find critical uncertainty reductions which must be resolved. An iterative methodology guides the resolution of uncertainties necessary to achieve desired levels of goal satisfaction, supporting trade-off analysis in the presence of uncertainty.