Locating White Box Reuse Via Data Mining

ion User 1. 2. 3. 4. 5. 6. 7. Figure 1: The Abstraction Technique 4 ing [1]. Hence, the attribute values are interfaces, which can be expanded to show further values. We will provide a three-dimensional view, similar to a drilling technique in executive information systems. As a demonstration, consider the feature-name example attribute. First pass of the data has indicated that two features may be candidate for abstraction. Both of these features are then selected for further analysis, revealing their attribute values. A second pass over this data identi es additional knowledge and assists the abstraction process. With a tuning aid approach [13], the technique highlights candidate modules for restructuring, allowing the user to request further analysis. The user then accepts and continues the abstraction, or rejects the suggestions. 4 Conclusion Reverse engineering of legacy code is mostly a manual process, aided by the assistance of tools. We have described the problems with understanding and comprehension of legacy code, and outlined the current state of reverse engineering research. The focus is to identify modular units (or objects), within legacy code, for either conversion to new systems, or restructuring of current systems. Abstraction or restructuring techniques are mostly manual. Our technique can be used for knowledge discovery of white box reuse in source code, candidate for redesign and abstraction to black box components. The technique, will not be limited to a speci c programming language, and can be modi ed for areas such as rule discovery in business process reengineering, and database mining. The system design incorporates user input to guide the discovery process. We have demonstrated that an all-purpose system, with an architectural approach of blackboard systems can be built, where the user acts as the controller. 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