Integrating Formal Predictions of Interactive System Behaviour with User Evaluation

It is well known that human error in the use of interactive devices can have severe safety or business consequences. It is important therefore that aspects of the design that compromise the usability of a device can be predicted before deployment. A range of techniques have been developed for identifying potential usability problems including laboratory based experiments with prototypes and paper based evaluation techniques. This paper proposes a framework that integrates experimental techniques with formal models of the device, along with assumptions about how the device will be used. Abstract models of prototype designs and use assumptions are analysed using model checking techniques. As a result of the analysis hypotheses are formulated about how a design will fail in terms of its usability. These hypotheses are then used in an experimental environment with potential users to test the predictions. Formal methods are therefore integrated with laboratory based user evaluation to give increased confidence in the results of the usability evaluation process. The approach is illustrated by exploring the design of an IV infusion pump designed for use in a hospital context.

[1]  Wayne D. Gray,et al.  The soft constraints hypothesis: a rational analysis approach to resource allocation for interactive behavior. , 2006, Psychological review.

[2]  John M. Rushby,et al.  Analyzing Cockpit Interfaces Using Formal Methods , 2001, FM-Everywhere@FORTE/PSTV.

[3]  J. Gregory Trafton,et al.  Memory for goals: an activation-based model , 2002, Cogn. Sci..

[4]  Ann Blandford,et al.  Verification-guided modelling of salience and cognitive load , 2008, Formal Aspects of Computing.

[5]  Jonathan Back,et al.  Choosing to interleave: human error and information access cost , 2012, CHI.

[6]  Kim J. Vicente,et al.  Programming errors contribute to death from patient-controlled analgesia: case report and estimate of probability , 2003, Canadian journal of anaesthesia = Journal canadien d'anesthesie.

[7]  Howard Bowman,et al.  Analysing Cognitive Behaviour using LOTOS and Mexitl , 1999, Formal Aspects of Computing.

[8]  Bernhard Beckert,et al.  A Method for Formalizing, Analyzing, and Verifying Secure User Interfaces , 2006, ICFEM.

[9]  Frank E. Ritter,et al.  Embodied models as simulated users: introduction to this special issue on using cognitive models to improve interface design , 2001, Int. J. Hum. Comput. Stud..

[10]  Philip J. Barnard,et al.  Interactions with Advanced Graphical Interfaces and the Deployment of Latent Human Knowledge , 1994, DSV-IS.

[11]  Maartje Gertruda Anna Ament The role of goal relevance in the occurrence of systematic slip errors in routine procedural tasks , 2011 .

[12]  Ellen J. Bass,et al.  Generating phenotypical erroneous human behavior to evaluate human-automation interaction using model checking , 2012, Int. J. Hum. Comput. Stud..