The Rise of Android Code Smells: Who Is to Blame?

International audienceThe 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

On the Survival of Android Code Smells in the Wild

International audienceThe 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

ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of Zoom and Spatial Biases in Image Classification

Image classifiers are information-discarding machines, by design. Yet, how these models discard information remains mysterious. We hypothesize that one way for image classifiers to reach high accuracy is to first zoom to the most discriminative region in the image and then extract features from there to predict image labels, discarding the rest of the image. Studying six popular networks ranging from AlexNet to CLIP, we find that proper framing of the input image can lead to the correct classification of 98.91% of ImageNet images. Furthermore, we uncover positional biases in various datasets, especially a strong center bias in two popular datasets: ImageNet-A and ObjectNet. Finally, leveraging our insights into the potential of zooming, we propose a test-time augmentation (TTA) technique that improves classification accuracy by forcing models to explicitly perform zoom-in operations before making predictions. Our method is more interpretable, accurate, and faster than MEMO, a state-of-the-art (SOTA) TTA method. We introduce ImageNet-Hard, a new benchmark that challenges SOTA classifiers including large vision-language models even when optimal zooming is allowed.Comment: NeurIPS 2023 Track on Datasets and Benchmark

Code Smells in iOS Apps: How do they compare to Android?

International audienceWith billions of app downloads, the Apple App Store and Google Play Store succeeded to conquer mobile devices. However, this success also challenges app developers to publish high-quality apps to keep attracting and satisfying end-users. In particular, taming the ever-growing complexity of mobile apps to cope with maintenance and evolution tasks under such a pressure may lead to bad development choices. While these bad choices, a.k.a. code smells, are widely studied in object-oriented software, their study in the context of mobile apps, and in particular iOS apps, remains in its infancy.Therefore, in this paper, we consider the presence of object-oriented and iOS-specific code smells by analyzing 279 open-source iOS apps. As part of this empirical study, we extended the Paprika toolkit, which was previously designed to analyze Android apps, in order to support the analysis of iOS apps developed in Objective-C or Swift. We report on the results of this analysis as well as a comparison between iOS and Android apps. We comment our findings related to the quality of apps in these two ecosystems. Interestingly, we observed that iOS apps tend to contain the same proportions of code smells regardless of the development language, but they seem to be less prone to code smells compared to Android apps

Comprendre les défauts de code spécifiques aux applications mobiles

Object-Oriented code smells are well-known concepts in software engineering. They refer to bad design and development practices commonly observed in software systems. With the emergence of mobile apps, new classes of code smells have been identified to refer to bad development practices that are specific to mobile platforms. These mobile-specific code smells differ from object-oriented ones by focusing on performance issues reported in the documentation or developer guidelines. Since their identification, many research works approached mobile-specific code smells to propose detection tools and study them. Nonetheless, most of these studies only focused on measuring the performance impact of such code smells and did not provide any insights about their motives and potential solutions. In particular, we lack knowledge about (i) the rationales behind the accrual of mobile code smells, (ii) the developers’ perception of mobile code smells, and (iii) the generalizability of code smells across different mobile platforms. These lacks hinder the understanding of mobile code smells and consequently prevent the design of adequate solutions for them. Therefore, we conduct in this thesis a series of empirical studies with the aim of understanding mobile code smells. First, we study the expansion of code smells in different mobile platforms. Then, we conduct a large-scale study to analyze the change history of mobile apps and discern the factors that favor the introduction and survival of code smells. To consolidate these studies, we also perform a user study to investigate developers’ perception of code smells and the adequacy of static analyzers as a solution for coping with them. Finally, we perform a qualitative study to question the established foundation about the definition and detection of mobile code smells. The results of these studies revealed important research findings. Notably, we showed that pragmatism, prioritization, and individual attitudes are not relevant factors for the accrual of mobile code smells. The problem is rather caused by ignorance and oversight, which are prevalent among mobile developers. Furthermore, we highlighted several flaws in the code smell definitions that are currently adopted by the research community. These results allowed us to elaborate some recommendations for researchers and tool makers willing to design detection and refactoring tools for mobile code smells. On top of that, our results opened perspectives for research works about the identification of mobile code smells and development practices in general.Au cours des dernières années, les applications mobiles sont devenues indispensables dans notre vie quotidienne. Ces applications ont pour particularité de fonctionner sur des téléphones mobiles, souvent limités en ressources (mémoire, puissance de calcul, batterie, etc). Ainsi, il est impératif de surveiller leur code source afin de s'assurer de l’absence de défauts de code, c.à.d., des pratiques de développement qui dégradent la performance. Plusieurs études ont été menées pour analyser les défauts de code des applications mobile et évaluer leur présence et leur impact sur la performance et l’efficience énergétique. Néanmoins, ces études n’ont pas examiné les caractéristiques et les motifs de ces défauts alors que ces éléments sont nécessaires pour la compréhension et la résolution de ce phénomène.L’objectif de cette thèse est de répondre à ce besoin en apportant des connaissances sur les défauts de code mobile. Pour cela, nous avons mené diverses études empiriques à caractère quantitatif et qualitatif pour comprendre ce phénomène et ses possibles résolutions. Les résultats de ces études montrent que les défauts de code mobile ne sont pas dus au pragmatisme, à la priorisation, ou aux comportements individuels des développeurs. En effet, l’essentielle raison derrière l’accumulation des défauts de code est l’ignorance générale de ces pratiques parmi les développeurs. Nos études ont aussi montré que le linter peut être un outil adéquat pour l’analyse des défauts de code et l’amélioration des performances. Cependant, certaines défauts nécessitent une analyse dynamique pour une détection plus précise. Enfin, nous avons montré qu’il existe un écart entre les défauts de code étudiés par la communauté scientifique et les réelles mauvaises pratiques adoptées par les développeurs d’applications mobiles. Pour remédier à cet écart, nous recommandons à la communauté d’impliquer les développeurs dans le processus d’identification de défauts de code

Comprendre les défauts de code spécifiques aux applications mobiles

Object-Oriented code smells are well-known concepts in software engineering. They refer to bad design and development practices commonly observed in software systems. With the emergence of mobile apps, new classes of code smells have been identified to refer to bad development practices that are specific to mobile platforms. These mobile-specific code smells differ from object-oriented ones by focusing on performance issues reported in the documentation or developer guidelines. Since their identification, many research works approached mobile-specific code smells to propose detection tools and study them. Nonetheless, most of these studies only focused on measuring the performance impact of such code smells and did not provide any insights about their motives and potential solutions. In particular, we lack knowledge about (i) the rationales behind the accrual of mobile code smells, (ii) the developers’ perception of mobile code smells, and (iii) the generalizability of code smells across different mobile platforms. These lacks hinder the understanding of mobile code smells and consequently prevent the design of adequate solutions for them. Therefore, we conduct in this thesis a series of empirical studies with the aim of understanding mobile code smells. First, we study the expansion of code smells in different mobile platforms. Then, we conduct a large-scale study to analyze the change history of mobile apps and discern the factors that favor the introduction and survival of code smells. To consolidate these studies, we also perform a user study to investigate developers’ perception of code smells and the adequacy of static analyzers as a solution for coping with them. Finally, we perform a qualitative study to question the established foundation about the definition and detection of mobile code smells. The results of these studies revealed important research findings. Notably, we showed that pragmatism, prioritization, and individual attitudes are not relevant factors for the accrual of mobile code smells. The problem is rather caused by ignorance and oversight, which are prevalent among mobile developers. Furthermore, we highlighted several flaws in the code smell definitions that are currently adopted by the research community. These results allowed us to elaborate some recommendations for researchers and tool makers willing to design detection and refactoring tools for mobile code smells. On top of that, our results opened perspectives for research works about the identification of mobile code smells and development practices in general.Au cours des dernières années, les applications mobiles sont devenues indispensables dans notre vie quotidienne. Ces applications ont pour particularité de fonctionner sur des téléphones mobiles, souvent limités en ressources (mémoire, puissance de calcul, batterie, etc). Ainsi, il est impératif de surveiller leur code source afin de s'assurer de l’absence de défauts de code, c.à.d., des pratiques de développement qui dégradent la performance. Plusieurs études ont été menées pour analyser les défauts de code des applications mobile et évaluer leur présence et leur impact sur la performance et l’efficience énergétique. Néanmoins, ces études n’ont pas examiné les caractéristiques et les motifs de ces défauts alors que ces éléments sont nécessaires pour la compréhension et la résolution de ce phénomène.L’objectif de cette thèse est de répondre à ce besoin en apportant des connaissances sur les défauts de code mobile. Pour cela, nous avons mené diverses études empiriques à caractère quantitatif et qualitatif pour comprendre ce phénomène et ses possibles résolutions. Les résultats de ces études montrent que les défauts de code mobile ne sont pas dus au pragmatisme, à la priorisation, ou aux comportements individuels des développeurs. En effet, l’essentielle raison derrière l’accumulation des défauts de code est l’ignorance générale de ces pratiques parmi les développeurs. Nos études ont aussi montré que le linter peut être un outil adéquat pour l’analyse des défauts de code et l’amélioration des performances. Cependant, certaines défauts nécessitent une analyse dynamique pour une détection plus précise. Enfin, nous avons montré qu’il existe un écart entre les défauts de code étudiés par la communauté scientifique et les réelles mauvaises pratiques adoptées par les développeurs d’applications mobiles. Pour remédier à cet écart, nous recommandons à la communauté d’impliquer les développeurs dans le processus d’identification de défauts de code

The Rise of Android Code Smells: Who Is to Blame?

International audienceThe 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

On the Survival of Android Code Smells in the Wild

International audienceThe 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

Android Code Smells: From Introduction to Refactoring

International audienceObject-oriented code smells are well-known concepts in software engineering that refer to bad design and development practices commonly observed in software systems. With the emergence of mobile apps, new classes of code smells have been identified by the research community as mobile-specific code smells. These code smells are presented as symptoms of important performance issues or bottlenecks. Despite the multiple empirical studies about these new code smells, their diffuseness and evolution along change histories remains unclear. We present in this article a large-scale empirical study that inspects the introduction, evolution, and removal of Android code smells. This study relies on data extracted from 324 apps, a manual analysis of 561 smell-removing commits, and discussions with 25 Android developers. Our findings reveal that the high diffuseness of mobile-specific code smells is not a result of releasing pressure. We also found that the removal of these code smells is generally a side effect of maintenance activities as developers do not refactor smell instances even when they are aware of them

On the Survival of Android Code Smells in the Wild

International audienceThe 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