This paper reports a method of assessing the implications for human error on system requirements, a topic not usually considered during requirements engineering (RE). In our previous work, we proposed a taxonomy of influencing factors that mightcontribute to human error. This paper takes the taxonomy and elaborates it to suggest generic requirements to deal with problems in different layers of the taxonomy. Components of the taxonomy are combined into a causal model for error, represented as aBayesian Belief Net (BBN). BBNs model the error influences arising from user knowledge, ability, and the task environment. These are combined with factors describing the complexity of action and user interface quality in scenarios of projected systemusage. The BBN model predicts probabilities of slips and mistakes. These are assessed according to action types in the scenario to suggest generic requirements to prevent the error or to deal with its consequences.
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