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Title: Software visualization in Prolog
Author: Grant, C. A. McK.
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2000
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Software visualization (SV) uses computer graphics to communicate the structure and behaviour of complex software and algorithms. One of the important issues in this field is how to specify SV, because existing systems are very cumbersome to specify and implement, which limits their effectiveness and hinders SV from being integrated into professional software development tools. In this dissertation the visualization process is decomposed into a series of formal mappings, which provides a formal foundation, and allows separate aspects of visualization to be specified independently. The first mapping specifies the information content of each view. The second mapping specifies a graphical representation of the information, and a third mapping specifies the graphical components that make up the graphical representation. By combining different mappings, completely different views can be generated. The approach has been implemented in Prolog to provide a very high level specification language for information visualization, and a knowledge engineering environment that allows data queries to tailor the information in a view. The output is generated by a graphical constraint solver that assembles the graphical components into a scene. This system provides a framework for SV called Vmax. Source code and run-time data are analyzed by Prolog to provide access to information about the program structure and run-time data for a wide range of highly interconnected browsable views. Different views and means of visualization can be selected from menus. An automatic legend describes each view, and can be interactively modified to customize how data is presented. A text window for editing source code is synchronized with the graphical view. Vmax is a complete Java development environment and end user SV system. Vmax compares favourably to existing SV systems in many taxonometric criteria, including automation, scope, information content, graphical output form, specification, tailorability, navigation, granularity and elision control. The performance and scalability of the new approach is very reasonable.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available