Author(s):  
Matthew L Bolton ◽  
Ellen J. Bass

Predicting failures in complex, human-interactive systems is difficult as they may occur under rare operational conditions and may be influenced by many factors including the system mission, the human operator's behavior, device automation, human-device interfaces, and the operational environment. This paper presents a method that integrates task analytic models of human behavior with formal models and model checking in order to formally verify properties of human-interactive systems. This method is illustrated with a case study: the programming of a patient controlled analgesia pump. Two specifications, one of which produces a counterexample, illustrate the analysis and visualization capabilities of the method.


Author(s):  
Meng Li ◽  
Sara Behdad ◽  
Matthew L. Bolton

Model checking is increasingly being used with task analytic behavior models to prove whether models of human-interactive systems are safe and reliable. Such methods could be used to predict how different types of users will choose to use system features. However, existing methods focus on modeling the full space of possible human behaviors without considering how users will choose to navigate this space. In this work, we present a new approach that enables model checking to predict how different types of users will use features of an interactive system by employing a novel combination of task analytic modeling and utility theory. This paper presents this method and illustrates its power with a smart thermostat application. The results of the application analysis and its implications for future research are discussed.


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