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Rapport (Rapport Technique) Année : 2023

ILLIMANI Memory Profiler -A Technical Report

Résumé

Modern programming languages provide automatic memory management with an efficient garbage collector making the memory management of an application transparent to the developer. There is a need for practical tools to support developers in their understanding of the memory consumption of their applications. In this paper, we present a prototype version of ILLIMANI: a precise object allocation profiler. It has a rich object model that provides information about the objects' allocation context, the evolution of memory usage, and garbage collector stress. We were able to find an object allocation site in the class UITHEME that was making 99,9% redundant allocations. We developed a Color Palette cache at the domain level that removed all the redundant allocations. We were also able to identify 2 other object allocation sites in the methods MAR-GIN»#INSETRECTANGLE and NUMBER»#ASMARGIN.
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hal-04225251 , version 1 (23-10-2023)

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  • HAL Id : hal-04225251 , version 1

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Sebastian Jordan Montaño, Guillermo Polito, Stéphane Ducasse, Pablo Tesone. ILLIMANI Memory Profiler -A Technical Report. INRIA Lille - Nord Europe. 2023. ⟨hal-04225251⟩
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