Characterising deprecated Android APIs

Li, Li; Gao, Jun; Bissyandé, Tegawendé F.; Ма, Лей; Xia, Xin; Klein, Jacques

doi:10.1145/3196398.3196419

Cited by 69 publications

(44 citation statements)

References 42 publications

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“…Bug fix commits study: Various studies have mined software repositories to analyze commits [66]- [69]. Purushothaman and Perry [70] studied patch-related commits in terms of sizes of bug fix hunks and repair action types to investigate the impact of small source code changes.…”

Section: Related Workmentioning

confidence: 99%

A Closer Look at Real-World Patches

Liu

Kim

Koyuncu

et al. 2018

2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Bug fixing is a time-consuming and tedious task. To reduce the manual efforts in bug fixing, researchers have presented automated approaches to software repair. Unfortunately, recent studies have shown that the state-of-the-art techniques in automated repair tend to generate patches only for a small number of bugs even with quality issues (e.g., incorrect behavior and nonsensical changes). To improve automated program repair (APR) techniques, the community should deepen its knowledge on repair actions from real-world patches since most of the techniques rely on patches written by human developers. Previous investigations on real-world patches are limited to statement level that is not sufficiently fine-grained to build this knowledge. In this work, we contribute to building this knowledge via a systematic and fine-grained study of 16,450 bug fix commits from seven Java open-source projects. We find that there are opportunities for APR techniques to improve their effectiveness by looking at code elements that have not yet been investigated. We also discuss nine insights into tuning automated repair tools. For example, a small number of statement and expression types are recurrently impacted by real-world patches, and expression-level granularity could reduce search space of finding fix ingredients, where previous studies never explored.

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Section: Related Workmentioning

confidence: 99%

A Closer Look at Real-World Patches

Liu

Kim

Koyuncu

et al. 2018

2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)

Self Cite

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“…As the world of software APIs expanded so did the number of studies on API usage and evolution [2], [22]- [37]. More recently, several research papers have been published on the Android API and its evolution [5], [6], [38]- [41]. The Android API is both large in code size and has numerous versions.…”

Section: Api Evolution Studiesmentioning

confidence: 99%

A3: Assisting Android API Migrations Using Code Examples

Lamothe

Shang

Chen

2022

IIEEE Trans. Software Eng.

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The fast-paced evolution of Android APIs has posed a challenging task for Android app developers. To leverage the newly and frequently released APIs from Android, developers often must spend considerable effort on API migrations. Prior research work and Android official documentation typically provide enough information to guide developers in identifying both the changed API calls that need to be migrated and the corresponding API calls in the new version of Android (what to migrate). However, the API migration task is still challenging since developers lack the knowledge of how to migrate the API calls. In addition to the official documentation, there exist code examples, such as Google Samples, that illustrate the usage of APIs. We posit that by analyzing the changes of API usage in code examples, we may be able to learn API migration patterns to assist developers with API migrations.In this paper, we propose an approach that automatically learns API migration patterns from code examples and applies these patterns to the source code of Android apps for API migration. To evaluate our approach, we migrate API calls in open source Android apps by learning API migration patterns from both public and manually generated code examples. We find that our approach can successfully learn API migration patterns and provide API migration assistance in 71 out of 80 cases. In particular, our approach can either automatically migrate API calls with little to no extra modifications needed or provide guidance to assist with the migrations. Our approach can be adopted by Android developers to reduce the effort they spend on regularly migrating Android APIs.

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“…We investigate the complexity evolution of Android apps via their release time 5 . State-of-the-art approaches for time-based evolution normally choose random apps for different timepoints.…”

Section: B Rq2: Complexity Evolution Via Timementioning

confidence: 99%

“…Consequently, to keep up, developers are engaged in a frenzy of updates [1], [2], [3], [4]. In general, developers update their apps for (1) keeping up with the evolution of Android APIs (e.g., discarding the use of deprecated ones [5] while accessing early-release ones [6]), (2) adapting to new requirements or providing new features to keep the app competitive, (3) fixing bugs that may cause runtime crashes, or that make the app vulnerable to security threats, (4) improving the performance or maintainability, either by removing unnecessary code or by refactoring existing functionalities.…”

Section: Introductionmentioning

confidence: 99%

On the Evolution of Mobile App Complexity

Gao

Bissyandé

et al. 2019

2019 24th International Conference on Engineering of Complex Computer Systems (ICECCS)

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Android developers are known to frequently update their apps for fixing bugs and addressing vulnerabilities, but more commonly for introducing new features. This process leads a trail in the ecosystem with multiple successive app versions which record historical evolutions of a variety of apps. While the literature includes various works related to such evolutions, little attention has been paid to the research question on how quality evolves, in particular with regards to maintainability and code complexity. In this work, we fill this gap by presenting a largescale empirical study: we leverage the AndroZoo dataset to obtain a significant number of app lineages (i.e., successive releases of the same Android apps), and rely on six well-established, maintainability-related complexity metrics commonly accepted in the literature on app quality, maintainability etc. Our empirical investigation eventually reveals that, overall, while Android apps become bigger in terms of code size as time goes by, the apps themselves appear to be increasingly maintainable and thus decreasingly complex.

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Characterising deprecated Android APIs

Cited by 69 publications

References 42 publications

A Closer Look at Real-World Patches

A Closer Look at Real-World Patches

A3: Assisting Android API Migrations Using Code Examples

On the Evolution of Mobile App Complexity

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