Rimvydas Ruksenas

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We present ongoing work to accommodate fine-grained analysis of interactive systems via model checking. We argue that this can be achieved by combining a basic abstract model of user behaviour and a separate constraint on the acceptable degree of cognitive mismatch. To explain the problem and illustrate our approach, we present a simple scenario related to(More)
We formally specify the interpretation stage in a dual state space human-computer interaction cycle. This is done by extending / re-organising our previous cognitive architecture. In particular, we focus on shape related aspects of the interpretation process associated with device input prompts. A cash-point example illustrates our approach. Using the SAL(More)
We define the predictability of a user interface as the property that an idealised user can predict with sufficient certainty the effect of any action in a given state in a system, where state information is inferred from the perceptible output of the system. In our definition, the user is not required to have full knowledge of a history of actions from an(More)
A demonstration is presented of how automated reasoning tools can be used to check the predictability of a user interface. Predictability concerns the ability of a user to determine the outcomes of their actions reliably. It is especially important in situations such as a hospital ward where medical devices are assumed to be reliable devices by their expert(More)
The correct functioning of interactive computer systems depends on both the faultless operation of the device and correct human actions. In this paper, we focus on system malfunctions due to human actions. We present abstract principles that generate cognitively plausible human behaviour. These principles are then formalised in a higher-order logic as a(More)
Well-designed interfaces use procedural and sensory cues to increase the cognitive salience of appropriate actions. However, empirical studies suggest that cognitive load can influence the strength of those cues. We formalise the relationship between salience and cognitive load revealed by empirical data. We add these rules to our abstract cognitive(More)
Designs can often be unacceptable on performance grounds. In this work, we integrate a GOMS-like ability to predict execution times into the generic cognitive architecture developed for the formal verification of human error related correctness properties. As a result, formal verification and GOMS-like timing analysis are combined within a unified(More)
Well-designed interfaces use procedural and sensory cues to increase the salience of appropriate actions and intentions. However, empirical studies suggest that cognitive load can influence the strength of procedural and sensory cues. We formalise the relationship between salience and cognitive load revealed by empirical data. We add these rules to our(More)