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
On the impact of UML analysis models on source-code comprehensibility and modifiability
ACM Transactions on Software Engineering and Methodology (TOSEM)
Cooperative clustering for software modularization
Journal of Systems and Software
To what extent can maintenance problems be predicted by code smell detection? - An empirical study
Information and Software Technology
Hi-index | 0.00 |
Antipatterns are “poor” solutions to recurring design problems which are conjectured in the literature to make object-oriented systems harder to maintain. However, little quantitative evidence exists to support this conjecture. We performed an empirical study to investigate whether the occurrence of antipatterns does indeed affect the understandability of systems by developers during comprehension and maintenance tasks. We designed and conducted three experiments, with 24 subjects each, to collect data on the performance of developers on basic tasks related to program comprehension and assessed the impact of two antipatterns and of their combinations: Blob and Spaghetti Code. We measured the developers’ performance with: (1) the NASA task load index for their effort, (2) the time that they spent performing their tasks, and, (3) their percentages of correct answers. Collected data show that the occurrence of one antipattern does not significantly decrease developers’ performance while the combination of two antipatterns impedes significantly developers. We conclude that developers can cope with one antipattern but that combinations of antipatterns should be avoided possibly through detection and refactorings.