A metric-based approach to detect abstract data types and state encapsulations

This article presents an approach to identify abstract data types (ADT) and abstract state encapsulations (ASE, also called abstract objects) in source code. This approach groups together functions, types, and variables into ADT and ASE candidates according to the proportion of features they share. The set of features considered includes the context of these elements, the relationships to their environment, and informal information. A prototype tool has been implemented to support this approach. It has been applied to three C systems (each between 30-38 Kloc). The ADTs and ASEs identified by the approach are compared to those identified by software engineers who did not know the proposed approach. In a case study, this approach has been shown to identify, in most cases, more ADTs and ASEs than five published techniques applied on the same systems. This is important when trying to identify as many ADTs and ASEs as possible.