A methodology to extract objects from procedural software
Moon-Kun Lee, Sung-Og Park · 2002
The paper presents a methodology to extract objects from procedural software. The methodology is the first phase in transforming procedural software to object oriented software. The methodology is based on the idea of generating all groups of object candidates with possible combinations and selecting a group with the best or optimal combination of candidates with respect to the degree of relativity and similarity between objects in the group and classes in a domain model. The methodology has innovative features in object extraction: a clustering method based on both static and dynamic clustering, the combinatorial cases of grouping object candidate cases based on abstraction, a refinement algorithm, a similarity algorithm for multiple n object and m classes, etc. This methodology provides reengineering experts with a comprehensive and integrated environment to select the best or optimal group of object candidates.