Towards a metrics suite for object oriented design
OOPSLA '91 Conference proceedings on Object-oriented programming systems, languages, and applications
Object-oriented metrics that predict maintainability
Journal of Systems and Software - Special issue on object-oriented software
Object-oriented metrics: measures of complexity
Object-oriented metrics: measures of complexity
Exploring the relationship between design measures and software quality in object-oriented systems
Journal of Systems and Software
The prediction of faulty classes using object-oriented design metrics
Journal of Systems and Software
The Confounding Effect of Class Size on the Validity of Object-Oriented Metrics
IEEE Transactions on Software Engineering
A Hierarchical Model for Object-Oriented Design Quality Assessment
IEEE Transactions on Software Engineering
Empirical Software Engineering
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Chidamber and Kemerer's Metrics Suite: A Measurement Theory Perspective
IEEE Transactions on Software Engineering
An Empirical Investigation of an Object-Oriented Software System
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
CSMR '01 Proceedings of the Fifth European Conference on Software Maintenance and Reengineering
Detecting Design Flaws via Metrics in Object-Oriented Systems
TOOLS '01 Proceedings of the 39th International Conference and Exhibition on Technology of Object-Oriented Languages and Systems (TOOLS39)
Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction
IEEE Transactions on Software Engineering
Subjective evaluation of software evolvability using code smells: An empirical study
Empirical Software Engineering
Journal of Systems and Software
Journal of Systems and Software
Visual Detection of Design Anomalies
CSMR '08 Proceedings of the 2008 12th European Conference on Software Maintenance and Reengineering
ACM SIGSOFT Software Engineering Notes
International Journal of Computer Applications in Technology
Tool for generating code metrics for C# source code using abstract syntax tree technique
ACM SIGSOFT Software Engineering Notes
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In order to improve software maintainability, possible improvement efforts must be made measurable. One such effort is refactoring the code which makes the code easier to read, understand and maintain. It is done by identifying the bad smell area in the code. This paper presents the results of an empirical study to develop a metrics model to identify the smelly classes. In addition, this metrics model is validated by identifying the smelly and error prone classes. The role of two new metrics (encapsulation and information hiding) is also investigated for identifying smelly and faulty classes in software code. This paper first presents a binary statistical analysis of the relationship between metrics and bad smells, the results of which show a significant relationship. Then, the metrics model (with significant metrics shortlisted from the binary analysis) for bad smell categorization (divided into five categories) is developed. To develop the model, three releases of the open source Mozila Firefox system are examined and the model is validated on one version of Mozila Sea Monkey, which has a strong industrial usage. The results show that metrics can predict smelly and faulty classes with high accuracy, but in the case of the categorized model, not all categories of bad smells can adequately be identified. Further, few categorised models can predict the faulty classes. Based on these results, we recommend more training for our model.