Publication Type
Journal Article
Version
acceptedVersion
Publication Date
3-2022
Abstract
The Android operating system is frequently updated, with each version bringing a new set of APIs. New versions may involve API deprecation; Android apps using deprecated APIs need to be updated to ensure the apps’ compatibility with old and new Android versions. Updating deprecated APIs is a time-consuming endeavor. Hence, automating the updates of Android APIs can be beneficial for developers. CocciEvolve is the state-of-the-art approach for this automation. However, it has several limitations, including its inability to resolve out-of-method variables and the low code readability of its updates due to the addition of temporary variables. In an attempt to further improve the performance of automated Android API update, we propose an approach named AndroEvolve, that addresses the limitations of CocciEvolve through the addition of data flow analysis and variable name denormalization. Data flow analysis enables AndroEvolve to resolve the value of any variable within the file scope. Variable name denormalization replaces temporary variables that may present in the CocciEvolve update with appropriate values in the target file. We have evaluated the performance of AndroEvolve and the readability of its updates on 372 target files containing 565 deprecated API usages. Each target file represents a file from an Android application that uses a deprecated API in its code. AndroEvolve successfully updates 481 out of 565 deprecated API invocations correctly, achieving an accuracy of 85.1%. Compared to CocciEvolve, AndroEvolve produces 32.9% more instances of correct updates. Moreover, our manual and automated evaluation shows that AndroEvolve updates are more readable than CocciEvolve updates.
Keywords
Android, API deprecation, API update, Data flow analysis, Program transformation, Readability
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
Empirical Software Engineering
Volume
27
Issue
3
First Page
1
Last Page
35
ISSN
1382-3256
Identifier
10.1007/s10664-021-10096-0
Publisher
Springer Verlag (Germany)
Citation
HARYONO, Stefanus A.; THUNG, Ferdian; LO, David; JIANG, Lingxiao; LAWALL, Julia; KANG, Hong Jin; SERRANO, Lucas; and MULLER, Gilles.
AndroEvolve: Automated Android API update with data flow analysis and variable denormalization. (2022). Empirical Software Engineering. 27, (3), 1-35.
Available at: https://ink.library.smu.edu.sg/sis_research/7092
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/s10664-021-10096-0