Cohesion and reuse in an object-oriented system
SSR '95 Proceedings of the 1995 Symposium on Software reusability
Object-oriented metrics: measures of complexity
Object-oriented metrics: measures of complexity
A Validation of Object-Oriented Design Metrics as Quality Indicators
IEEE Transactions on Software Engineering
An Evaluation of the MOOD Set of Object-Oriented Software Metrics
IEEE Transactions on Software Engineering
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
A Unified Framework for Cohesion Measurement in Object-OrientedSystems
Empirical Software Engineering
Empirical Software Engineering
A Critical Analysis of Current OO Design Metrics
Software Quality Control
Chidamber and Kemerer's Metrics Suite: A Measurement Theory Perspective
IEEE Transactions on Software Engineering
Measuring Design-Level Cohesion
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
Evaluating the Impact of Object-Oriented Design on Software Quality
METRICS '96 Proceedings of the 3rd International Symposium on Software Metrics: From Measurement to Empirical Results
Measuring OO Systems: A Critical Analysis of the MOOD Metrics
TOOLS '99 Proceedings of the Technology of Object-Oriented Languages and Systems
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
Improved Metrics for Encapsulation Based on Information Hiding
ICYCS '08 Proceedings of the 2008 The 9th International Conference for Young Computer Scientists
Metric based testability model for object oriented design (MTMOOD)
ACM SIGSOFT Software Engineering Notes
Visual Detection of Design Anomalies
CSMR '08 Proceedings of the 2008 12th European Conference on Software Maintenance and Reengineering
An exploratory study of the impact of antipatterns on class change- and fault-proneness
Empirical Software Engineering
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
Quality-Aware Refactoring for Early Detection and Resolution of Energy Deficiencies
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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To assist maintenance and evolution teams, work needs to be done at the onset of software development. One such facilitation is refactoring the code, making it easier to read, understand and maintain. Refactoring is done by identifying bad smell areas in the code. In this paper, based on empirical analysis, we develop a metrics model to identify smelly 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 thev 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 verify our model, we examine the open source Firefox system, which has a strong industrial usage. The results show that proposed metrics model for bad smell can predict faulty classes with high accuracy, but in the case of the categorized model not all categories of bad smells can adequately identified the faulty and smelly classes. Due to certain limitations of our study more experiments are required to generalize the results of bad smell and faulty class identification in software code.