ReVis: Reverse Engineering by Clustering and Visual Object Classification

  • Authors:
  • Aaron J. Quigley;Margot Postema;Heinz Schmidt

  • Affiliations:
  • -;-;-

  • Venue:
  • ASWEC '00 Proceedings of the 2000 Australian Software Engineering Conference
  • Year:
  • 2000

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper presents the framework of a scale-oriented scheme for the presentation and classification of reverse engineered sections of procedural code into objects. The aim is to develop an extensible system framework, which allows the output from a suite of data analysis tools to be visually presented to a user.The relationship between the analysis and visualization is a progressive cycle, where each time through the cycle the overall quality of the classified objects improves. This framework supports two distinct methods of information feedback from the visualization to the analysis suite. The two feedback loops aim to increase both the ease of understanding for the reverse engineer and the quality of the resultant objects. As the analyst, views the visualization the perceived view of the relationships exhibited in the system may be modified, removed or added to. This results in a change to the underlying graph or the clustering of that graph, which must be addressed in the visual presentation of the information using a variety of techniques to maintain the users.