On the reuse and recommendation of model refactoring specifications

Reimann, Jan; Seifert, Mirko; ABmann, Uwe

doi:10.1007/s10270-012-0243-2

Cited by 18 publications

(14 citation statements)

References 16 publications

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“…They are reported to have a negative impact on properties, such as efficiency, user experience or security. Reimann et al are also offering the detection and correction of code smells via the REFACTORY tool [58]. This tool can detect code smells from an Eclipse Modeling Framework (EMF) model.…”

Section: Related Workmentioning

confidence: 99%

Code Smells in iOS Apps: How Do They Compare to Android?

Habchi

Hecht

Rouvoy

et al. 2017

2017 IEEE/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft)

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Section: Related Workmentioning

confidence: 99%

Code Smells in iOS Apps: How Do They Compare to Android?

Habchi

Hecht

Rouvoy

et al. 2017

2017 IEEE/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft)

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“…After the definition of these code smells, many research works proposed tools and approaches for detecting them [25], [27], [43], [47]. Reimann et al offered a tool called REFACTORY for the detection and correction of code smells [49]. Afterwards, Hecht et al [24] proposed PAPRIKA, a tooled approach that detects OO and Android code smells in Android apps.…”

Section: Related Workmentioning

confidence: 99%

On the Survival of Android Code Smells in the Wild

Habchi

Rouvoy

Moha

2019

2019 IEEE/ACM 6th International Conference on Mobile Software Engineering and Systems (MOBILESoft)

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The success of smartphones and app stores have contributed to the explosion of the number of mobile apps proposed to end-users. In this very competitive market, developers are rushed to regularly release new versions of their apps in order to retain users. Under such pressure, app developers may be tempted to adopt bad design or implementation choices, leading to the introduction of code smells. Mobile-specific code smells represent a real concern in mobile software engineering. Many studies have proposed tools to automatically detect their presence and quantify their impact on performance. However, there remains-so far-no evidence about the lifespan of these code smells in the history of mobile apps. In this paper, we present the first large-scale empirical study that investigates the survival of Android code smells. This study covers 8 types of Android code smells, 324 Android apps, 255k commits, and the history of 180k code smell instances. Our study reports that while in terms of time Android code smells can remain in the codebase for years before being removed, it only takes 34 effective commits to remove 75% of them. Also, Android code smells disappear faster in bigger projects with higher releasing trends. Finally, we observed that code smells that are detected and prioritised by linters tend to disappear before other code smells.

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“…Refactoring GT 2010 none [41] Sim [186] Observer* Reactive none 2008 none [187] Visitor* Higher-order QVT-O 2012 none [189] Ent. Merge Abstraction QVT-O 2014 none [188] Generic Trans. Refactoring EMFText 2013 none [190] Transformation Chain* Analysis ATL 2009 [132] [191] Struc.…”

Section: Take Down Policymentioning

confidence: 99%