A3: Assisting Android API Migrations Using Code Examples

Abstract

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.

Semantic Patches for Adaptation of JavaScript Programs to Evolving Libraries

“…The same applies to the gofix tool for G o. 10 Others have also looked at ways to automatically compute differences between library versions, and based on these differences either suggest changes for adapting clients to breaking changes in the APIs or directly transform the client code as with JSFIX [7,8,9,10,11,12]. M ost of these approaches are for Java, where each member of a class has a fully qualified name, which makes it tractable to compute differences on a type-level between two versions of a Java API, and thereby automatically identify many breaking changes.…”

MLCatchUp: Automated Update of Deprecated Machine-Learning APIs in Python

“…Rather, developers need to manually perform the transformations based on the examples and information produced by Diff-CatchUp. A4 [8] automatically assists Android API migrations by learning API migration patterns from code examples. AppEvolve [9] automates API-usage update for Android, creating patches from before-and after-update code examples.…”

“…Several studies have attempted to automate updates process of deprecated API usages [8]- [11]. However, prior works mainly target Java programs, and no study has attempted to automate the update for Python deprecated API usages.…”

APIMigrator

“…APIMigrator primarily relates to example-based program transformation techniques (e.g., [1,13,16,18,20,21,23]). APIMigrator differs from some of these techniques [1,16,18,20,21] in that it uses a more general approach to identify when a migration patch is applicable.…”

“…This makes our tool effective in using examples from different codebases. As opposed to A4 [13], APIMigrator identifies migration examples in remote repositories, handles changes in return values, and is able to prioritize migration examples. Finally, unlike Meditor [23], APIMigrator can analyze and compare multiple examples while performing migrations, allowing for prioritizing and using migration patches that are closer to the essence of the required changes.…”