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Android Runtime (ART), which is the standard application runtime environment, has a garbage collection (GC) function. ART have an implementation of generational GC. The GC clusters objects into two groups, which are the young and old generations. An object in the young generation is promoted into an old object after passing several times of GC executions. In this paper, we propose to adjust the promoting condition based on the object feature, which is the size of each object. We then evaluate our proposed method and demonstrate that our method based on the feature can reduce the memory consumption of applications with smaller performance decline than the method without feature consideration.

Promotion Condition Optimization based on Application Features in Generational GC of Android Application Runtime