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Mike Brayshaw

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Publications by Mike Brayshaw (bibliography)

1993

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Brayshaw, Mike (1993): MRE: A Flexible and Customisable Program Visualisation Architecture. In: Alty, James L., Diaper, Dan and Guest, D. (eds.) Proceedings of the Eighth Conference of the British Computer Society Human Computer Interaction Specialist Group - People and Computers VIII August 7-10, 1993, Loughborough University, UK. pp. 425-439.

“In this paper we will look to extend basic visual metaphors to produce higher level descriptions of program execution that allow users to express their own perspectives on a task. We shall show how this can be done by adapting a model of event recognition using agents, demonstrate how these agents are useful in their own right, and then embed such definitions within templates to generate new visualisations. The aim is thus to bring increased flexibility and expressibility to programmers in order to aid software tool based problem solving, enable them to build increasingly abstract models of their domain, and debug programs from this particular perspective level. The above will be presented within the context of an overall debugging model, and its integration demonstrated.”

1991

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Brayshaw, Mike and Eisenstadt, Marc (1991): A Practical Graphical Tracer for Prolog. In International Journal of Man-Machine Studies, 35 (5) pp. 597-631.

“We describe a practical and enhanced implementation of a graphical Prolog tracer which not only provides a faithful (slow-motion) representation of the inner workings of the Prolog interpreter, but also allows a high-speed visual overview of execution for rapidly homing in on buggy code. The current work extends our original "Transparent Prolog Machine" in the following ways: (a) complex unification histories for given variables can be displayed; (b) cross-variable dependencies (sharing) across widely-dispersed sections of code can be highlighted; (c) an earlier defect, wherein a given user could write code which defeated the speed/size of the current fastest/largest display capability (i.e. a "horizon effect") is dealt with; (d) users of textual (Byrd Box) tracers are provided with an upward-compatible migration pathway; (e) code can be traced either "live" or "retrospectively" at different grains of detail. We distinguish among four different ways of manipulating the "navigational space" produced by large Prolog programs: (a) by granularity i.e. coarse-grained vs fine-grained; (b) by scale, i.e. close-up vs far away (c) by compression, i.e. the use of a single compact display region or symbol to indicate "additional territory", at the same granularity and scale; (d) by abstraction, i.e. a movement away from the raw Prolog code and towards a representation closer to the programmer's own plans and intentions. The paper includes detailed examples of the tracer in action.”

1989

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Brayshaw, Mike, Domingue, John and Rajan, Tim (1989): An Integrated Approach to Monitoring the Behaviour and Performance of Inference Systems. In: Sutcliffe, Alistair G. and Macauley, Linda (eds.) Proceedings of the Fifth Conference of the British Computer Society Human Computer Interaction Specialist Group - People and Computers V August 5-8, 1989, University of Nottingham, UK. pp. 409-425.

“Recent research into the graphical visualization of program behaviour has contributed to program development by enabling the programmer to see immediately the direct implications of coding decisions. This presentation technique is based on the same principles as WYSIWYG word processors and electronic publishing packages which ease publishing by allowing the editor to see both the large and fine-grained implications of page and subsection layout. However, the behaviour of programs is only a part of the programmers job. Once the behaviour has been finalized the task of performance analysis starts, where the programmer fine tunes the program in order to determine the most efficient representation. To extend the benefits of program visualization to the task of performance enhancement, this paper presents an integrated approach to the visualization of both program behaviour and performance, building on our previous research into visualization of the behaviour of inference systems. Users can view the details of performance metrics at a chosen level of grain-size, and in addition be able to interpret the statistics in terms of the behaviour of the program. This enables users to rapidly find performance problems with long distance views, and then home in on the specific details using a close-up view. Performance may be monitored in several different ways, and can also be customized by the user. The result combines the graphical tracing of the behaviour of a program with statistical measurements of its performance, providing the developer with an integrated picture of program execution in one display.”

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