Methodology to extract objects from procedural software

This 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 combination 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.