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The Android operating system is frequently updated, with each versionbringing a new set of APIs. New versions may involve API deprecation; Androidapps using deprecated APIs need to be updated to ensure the apps' compatibilitywithold and new versions of Android. Updating deprecated APIs is atime-consuming endeavor. Hence, automating the updates of Android APIs can bebeneficial for developers. CocciEvolve is the state-of-the-art approach forthis automation. However, it has several limitations, including its inabilityto resolve out-of-method-boundary variables and the low code readability of itsupdate due to the addition of temporary variables. In an attempt to furtherimprove the performance of automated Android API update, we propose an approachnamed AndroEvolve, which addresses the limitations of CocciEvolve through theaddition of data flow analysis and variable name denormalization. Data flowanalysis enables AndroEvolve to resolve the value of any variable within thefile scope. Variable name denormalization replaces temporary variables that maypresent in the CocciEvolve update with appropriate values in the target file.We have evaluated the performance of AndroEvolve and the readability of itsupdates on 360 target files. AndroEvolve produces 26.90% more instances ofcorrect updates compared to CocciEvolve. Moreover, our manual and automatedevaluation shows that AndroEvolve updates are more readable than CocciEvolveupdates.

AndroEvolve: Automated Android API Update with Data Flow Analysis and Variable Denormalization