Detecting Resource Leaks on Android with Alpakka

Mobile devices have become integral to our everyday lives, yet their utility hinges on their battery life. In Android apps, resource leaks caused by inefficient resource management are a significant contributor to battery drain and poor user experience. Our work introduces Alpakka, a source-to-source compiler for Android's Smali syntax. To showcase Alpakka's capabilities, we developed an Alpakka library capable of detecting and automatically correcting resource leaks in Android APK files. We demonstrate Alpakka's effectiveness through empirical testing on 124 APK files from 31 real-world Android apps in the DroidLeaks [12] dataset. In our analysis, Alpakka identified 93 unique resource leaks, of which we estimate 15% are false positives. From these, we successfully applied automatic corrections to 45 of the detected resource leaks.

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Publication Details

Published
2025-06-12
DOI
https://doi.org/10.1145/3732771.3742724
Primary Topic
Advanced Malware Detection Techniques
Type
article
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article

Detecting Resource Leaks on Android with Alpakka

João Bispo, Alexandra Mendes, Gustavo Soares Santos
Advanced Malware Detection Techniques
article

Detecting Resource Leaks on Android with Alpakka

João Bispo, Alexandra Mendes, Gustavo Soares Santos
article en

Abstract

Mobile devices have become integral to our everyday lives, yet their utility hinges on their battery life. In Android apps, resource leaks caused by inefficient resource management are a significant contributor to battery drain and poor user experience. Our work introduces Alpakka, a source-to-source compiler for Android's Smali syntax. To showcase Alpakka's capabilities, we developed an Alpakka library capable of detecting and automatically correcting resource leaks in Android APK files. We demonstrate Alpakka's effectiveness through empirical testing on 124 APK files from 31 real-world Android apps in the DroidLeaks [12] dataset. In our analysis, Alpakka identified 93 unique resource leaks, of which we estimate 15% are false positives. From these, we successfully applied automatic corrections to 45 of the detected resource leaks.

Universidade do Porto (PT), INESC TEC (PT)
Openalex Percentile: Top 84%
Advanced Malware Detection Techniques
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Detecting Resource Leaks on Android with Alpakka — João Bispo, Alexandra Mendes, et al. · (2025) | TGRS Research Map | TGRS