Is a strategy for code smell assessment long overdue?
Proceedings of the 2010 ICSE Workshop on Emerging Trends in Software Metrics
An exploratory study of code smells in evolving aspect-oriented systems
Proceedings of the tenth international conference on Aspect-oriented software development
Investigating the impact of design debt on software quality
Proceedings of the 2nd Workshop on Managing Technical Debt
Which code construct metrics are symptoms of post release failures?
Proceedings of the 2nd International Workshop on Emerging Trends in Software Metrics
Nothing else matters: what predictive model should I use?
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
An exploratory study of the impact of antipatterns on class change- and fault-proneness
Empirical Software Engineering
Proceedings of the 11th annual international conference on Aspect-oriented Software Development
Exploring the impact of inter-smell relations on software maintainability: an empirical study
Proceedings of the 2013 International Conference on Software Engineering
Hunting for smells in natural language tests
Proceedings of the 2013 International Conference on Software Engineering
To what extent can maintenance problems be predicted by code smell detection? - An empirical study
Information and Software Technology
Investigating the evolution of code smells in object-oriented systems
Innovations in Systems and Software Engineering
| Hi-index | 0.00 |
Code smells are poor implementation choices, thought to make object-oriented systems hard to maintain. In this study, we investigate if classes with code smells are more change-prone than classes without smells. Specifically, we test the general hypothesis: classes with code smells are not more change prone than other classes. We detect 29 code smells in 9 releases of Azureus and in 13 releases of Eclipse, and study the relation between classes with these code smells and class change-proneness. We show that, in almost all releases of Azureus and Eclipse, classes with code smells are more change-prone than others, and that specific smells are more correlated than others to change-proneness. These results justify a posteriori previous work on the specification and detection ofcode smells and could help focusing quality assurance and testing activities.