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The rise of mobile apps as new software systems led to the emergence of new development requirements regarding performance. Development practices that do not respect these requirements can seriously hinder app performances and impair user experience, they qualify as code smells. Mobile code smells are generally associated with inexperienced developers who lack knowledge about the framework guidelines. However, this assumption remains unverified and there is no evidence about the role played by developers in the accrual of mobile code smells. In this paper, we therefore study the contributions of developers related to Android code smells. To support this study, we propose SNIFFER, an open-source toolkit that mines Git repositories to extract developers’ contributions as code smell histories. Using SNIFFER, we analysed 255k commits from the change history of 324 Android apps. We found that the ownership of code smells is spread across developers regardless of their seniority. There are no distinct groups of code smell introducers and removers. Developers who introduce and remove code smells are mostly the same.
mobile apps, [INFO.INFO-MC] Computer Science [cs]/Mobile Computing, Android, [INFO.INFO-SE] Computer Science [cs]/Software Engineering [cs.SE], code smells, [INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing, history mining
mobile apps, [INFO.INFO-MC] Computer Science [cs]/Mobile Computing, Android, [INFO.INFO-SE] Computer Science [cs]/Software Engineering [cs.SE], code smells, [INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing, history mining
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |