Studying the evolution of software through software clustering and concept analysis

This thesis describes an investigation into the use of software clustering and concept analysis techniques for studying the evolution of software. These techniques produce representations of software systems by clustering similar entities in the system together. The software engineering community has used these techniques for a number of different reasons but this is the first study to investigate their uses for evolution. The representations produced by software clustering and concept analysis techniques can be used to trace changes to a software system over a number of different versions of the system. This information can be used by system maintainers to identify worrying evolutionary trends or assess a proposed change by comparing it to the effects of an earlier, similar change. The work described here attempts to establish whether the use of software clustering and concept analysis techniques for studying the evolution of software is worth pursuing. Four techniques, chosen based on an extensive literature survey of the field, have been used to create representations of versions of a test software system. These representations have been examined to assess whether any observations about the evolution of the system can be drawn from them. The results are positive and it is thought that evolution of software systems could be studied by using these techniques

Society. A Metric-based Approach to Detect Abstract Data Types and State Encapsulations

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. 1

A Metric-based Approach to Detect Abstract Data Types and State Encapsulations Jean-François Girard

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. 1