Parametric prediction of heap memory requirements

This work presents a technique to compute symbolic polynomial approximations of the amount of dynamic memory required to safely execute a method without running out of memory, for Javalike imperative programs. We consider object allocations and deallocations made by the method and the methods it tra...

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Detalles Bibliográficos
Autores principales:	Braberman, Víctor Adrián, Fernández, Federico Javier, Garbervetsky, Diego
Publicado:	2008
Materias:	Heap consumption Heap space analysis Java Memory regions Bernstein bases Dynamic memories Imperative programs Initial configurations Life-times Memory consumptions Memory managements Memory requirements Object allocations Out of memories Polyhedral domains Polynomial optimization problems Polynomial approximation
Acceso en línea:	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97816055_v_n_p141_Braberman http://hdl.handle.net/20.500.12110/paper_97816055_v_n_p141_Braberman
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	paper:paper_97816055_v_n_p141_Braberman
record_format	dspace
spelling	paper:paper_97816055_v_n_p141_Braberman2023-06-08T16:38:09Z Parametric prediction of heap memory requirements Braberman, Víctor Adrián Fernández, Federico Javier Garbervetsky, Diego Heap consumption Heap space analysis Java Memory regions Bernstein bases Dynamic memories Heap consumption Heap space analysis Imperative programs Initial configurations Java Life-times Memory consumptions Memory managements Memory regions Memory requirements Object allocations Out of memories Polyhedral domains Polynomial optimization problems Polynomial approximation This work presents a technique to compute symbolic polynomial approximations of the amount of dynamic memory required to safely execute a method without running out of memory, for Javalike imperative programs. We consider object allocations and deallocations made by the method and the methods it transitively calls. More precisely, given an initial configuration of the stack and the heap, the peak memory consumption is the maximum space occupied by newly created objects in all states along a run from it. We over-approximate the peak memory consumption using a scoped-memory management where objects are organized in regions associated with the lifetime of methods. We model the problem of computing the maximum memory occupied by any region configuration as a parametric polynomial optimization problem over a polyhedral domain and resort to Bernstein basis to solve it. We apply the developed tool to several benchmarks.Copyright © 2008 ACM. Fil:Braberman, V. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Fernández, F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Garbervetsky, D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2008 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97816055_v_n_p141_Braberman http://hdl.handle.net/20.500.12110/paper_97816055_v_n_p141_Braberman
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Heap consumption Heap space analysis Java Memory regions Bernstein bases Dynamic memories Heap consumption Heap space analysis Imperative programs Initial configurations Java Life-times Memory consumptions Memory managements Memory regions Memory requirements Object allocations Out of memories Polyhedral domains Polynomial optimization problems Polynomial approximation
spellingShingle	Heap consumption Heap space analysis Java Memory regions Bernstein bases Dynamic memories Heap consumption Heap space analysis Imperative programs Initial configurations Java Life-times Memory consumptions Memory managements Memory regions Memory requirements Object allocations Out of memories Polyhedral domains Polynomial optimization problems Polynomial approximation Braberman, Víctor Adrián Fernández, Federico Javier Garbervetsky, Diego Parametric prediction of heap memory requirements
topic_facet	Heap consumption Heap space analysis Java Memory regions Bernstein bases Dynamic memories Heap consumption Heap space analysis Imperative programs Initial configurations Java Life-times Memory consumptions Memory managements Memory regions Memory requirements Object allocations Out of memories Polyhedral domains Polynomial optimization problems Polynomial approximation
description	This work presents a technique to compute symbolic polynomial approximations of the amount of dynamic memory required to safely execute a method without running out of memory, for Javalike imperative programs. We consider object allocations and deallocations made by the method and the methods it transitively calls. More precisely, given an initial configuration of the stack and the heap, the peak memory consumption is the maximum space occupied by newly created objects in all states along a run from it. We over-approximate the peak memory consumption using a scoped-memory management where objects are organized in regions associated with the lifetime of methods. We model the problem of computing the maximum memory occupied by any region configuration as a parametric polynomial optimization problem over a polyhedral domain and resort to Bernstein basis to solve it. We apply the developed tool to several benchmarks.Copyright © 2008 ACM.
author	Braberman, Víctor Adrián Fernández, Federico Javier Garbervetsky, Diego
author_facet	Braberman, Víctor Adrián Fernández, Federico Javier Garbervetsky, Diego
author_sort	Braberman, Víctor Adrián
title	Parametric prediction of heap memory requirements
title_short	Parametric prediction of heap memory requirements
title_full	Parametric prediction of heap memory requirements
title_fullStr	Parametric prediction of heap memory requirements
title_full_unstemmed	Parametric prediction of heap memory requirements
title_sort	parametric prediction of heap memory requirements
publishDate	2008
url	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97816055_v_n_p141_Braberman http://hdl.handle.net/20.500.12110/paper_97816055_v_n_p141_Braberman
work_keys_str_mv	AT brabermanvictoradrian parametricpredictionofheapmemoryrequirements AT fernandezfedericojavier parametricpredictionofheapmemoryrequirements AT garbervetskydiego parametricpredictionofheapmemoryrequirements
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Parametric prediction of heap memory requirements

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