Scenario-Based Assessment of Nonfunctional Requirements
IEEE Transactions on Software Engineering
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This paper addresses the problem of requirements engiineering for complex socio-technical systems where an optimal set of technology components and human operators have to be selected to achieve system goals. Goals are achieved by tasks that are expressed as operational scenarios with variations in environmental conditions. The approach taken is to develop a probabilistic model of system reliability as a Bayesian Belief Network (BBN). The BBN model predicts human and machine reliabilities, given input variables representing the scenario and ranges of environmental conditions (i.e., weather, climate, etc.). A software tool, the System Reliability Analyser (SRA) is described that runs a set of scenarios against the BBN models while systematically varying the ranges of 12 input variables specifying properties of human operators such as training, technical equipment specification and environmental conditions. The tool reports human and technical equipment specifications that "survive" thescenario testing at a reliability level higher than a user-defined level (e.g., failure probability p