Refactoring: improving the design of existing code
Refactoring: improving the design of existing code
Object-Oriented Design Heuristics
Object-Oriented Design Heuristics
Bad Smells " Humans as Code Critics
ICSM '04 Proceedings of the 20th IEEE International Conference on Software Maintenance
Object-Oriented Metrics in Practice
Object-Oriented Metrics in Practice
Subjective evaluation of software evolvability using code smells: An empirical study
Empirical Software Engineering
Drivers for software refactoring decisions
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Journal of Systems and Software
The evolution and impact of code smells: A case study of two open source systems
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
Building empirical support for automated code smell detection
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
ICSM '10 Proceedings of the 2010 IEEE International Conference on Software Maintenance
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Context: The concept of code smells is widespread in Software Engineering. However, in spite of the many discussions and claims about them, there are few empirical studies to support or contest these ideas. In particular, the study of the human perception of what is a code smell and how to deal with it has been mostly neglected. Objective: To build empirical support to understand the effect of god classes, one of the most known code smells. In particular, this paper focuses on how conceptualization affects identification of god classes, i.e., how different people perceive the god class concept. Method: A controlled experiment that extends and builds upon another empirical study about how humans detect god classes [19]. Our study: i) deepens and details some of the research questions of the previous study, ii) introduces a new research question and, iii) when possible, compares the results of both studies. Result: Our findings show that participants have different personal criteria and preferences in choosing drivers to identify god classes. The agreement between participants is not high, which is in accordance with previous studies. Conclusion: This study contributes to expand the empirical data about the human perception of code smells. It also presents a new way to evaluate effort and distraction in experiments through the use of automatic logging of participant actions.