Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems

• Published in: IEEE transactions on software engineering Vol. 34; no. 2; pp. 287 - 300
• Main Authors: Marcus, A., Poshyvanyk, D., Ferenc, R.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2008; IEEE Computer Society
• Subjects: and reengineering; Automation; Case studies; Code documentation; Coherence; Cohesion; Computational linguistics; Computer programs; Current measurement; Digital Object Identifier; Document analysis; Document indexing; Faults; Information analysis; Information retrieval; Information systems; Language; Maintainability; Mathematical models; Metrics/Measurement; Natural language; Object oriented; Object-oriented programming; Open source software; Particle measurements; Psychology; Quality analysis and evaluation; Restructuring; reverse engineering; Semantics; Software; Software engineering; Software maintenance; Software measurement; Software quality; Software systems; Source code; Studies; Document indexing; Metrics/Measurement; and reengineering; Quality analysis and evaluation; reverse engineering; Maintainability; Restructuring; Document analysis; Code documentation
• ISSN: 0098-5589; 1939-3520
• DOI: 10.1109/TSE.2007.70768

High cohesion is a desirable property of software as it positively impacts understanding, reuse, and maintenance. Currently proposed measures for cohesion in Object-Oriented (OO) software reflect particular interpretations of cohesion and capture different aspects of it. Existing approaches are largely based on using the structural information from the source code, such as attribute references, in methods to measure cohesion. This paper proposes a new measure for the cohesion of classes in OO software systems based on the analysis of the unstructured information embedded in the source code, such as comments and identifiers. The measure, named the Conceptual Cohesion of Classes (C3), is inspired by the mechanisms used to measure textual coherence in cognitive psychology and computational linguistics. This paper presents the principles and the technology that stand behind the C3 measure. A large case study on three open source software systems is presented which compares the new measure with an extensive set of existing metrics and uses them to construct models that predict software faults. The case study shows that the novel measure captures different aspects of class cohesion compared to any of the existing cohesion measures. In addition, combining C3 with existing structural cohesion metrics proves to be a better predictor of faulty classes when compared to different combinations of structural cohesion metrics.