Quantitative dynamic-memory analysis for Java

Space- and time-predictability are hard to achieve for object-oriented languages with automated dynamic-memory management. Although there has been significant work to design APIs, such as the Real-Time Specification for Java (RTSJ), and to implement garbage collectors to enable real-time performance...

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Autores principales: Garbervetsky, D., Yovine, S., Braberman, V., Rouaux, M., Taboada, A.
Formato: JOUR
Materias:
Java real-time
quantitative memory requirements
scoped-memory
static analysis
Aircraft collisions
Analysis techniques
Closed form
Compile time
Dynamic memory
Free memory
Garbage collectors
Memory organizations
Memory requirements
Memory usage
Object-oriented languages
Program variables
Real time performance
Real-time specification for javas
Semi-automatics
Space analysis
Upper Bound
Aircraft accidents
Automatic programming
Java programming language
Static analysis
Time series analysis
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_15320626_v23_n14_p1665_Garbervetsky
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_15320626_v23_n14_p1665_Garbervetsky
record_format dspace
spelling todo:paper_15320626_v23_n14_p1665_Garbervetsky2023-10-03T16:21:30Z Quantitative dynamic-memory analysis for Java Garbervetsky, D. Yovine, S. Braberman, V. Rouaux, M. Taboada, A. Java real-time quantitative memory requirements scoped-memory static analysis Aircraft collisions Analysis techniques Closed form Compile time Dynamic memory Free memory Garbage collectors Java real-time Memory organizations Memory requirements Memory usage Object-oriented languages Program variables Real time performance Real-time specification for javas scoped-memory Semi-automatics Space analysis Upper Bound Aircraft accidents Automatic programming Java programming language Static analysis Time series analysis Space- and time-predictability are hard to achieve for object-oriented languages with automated dynamic-memory management. Although there has been significant work to design APIs, such as the Real-Time Specification for Java (RTSJ), and to implement garbage collectors to enable real-time performance, quantitative space analysis is still in its infancy. This work presents the integration of a series of compile-time analysis techniques to help predicting quantitative memory usage. In particular, we focus on providing tool assistance for identifying RTSJ scoped-memory regions, their sizes, and overall memory usage. First, the tool-suite synthesizes a memory organization where regions are associated with methods. Second, it infers their sizes in parametric closed form in terms of relevant program variables. Third, it exhibits a parametric upper bound on the amount of available free memory required to execute a method. The experiments carried out with a RTSJ benchmark, a real-time aircraft collision detector, show that semi-automatic, tool-assisted generation of scoped-based code is both helpful and doable. © 2010 John Wiley & Sons, Ltd. Fil:Garbervetsky, D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Braberman, V. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Rouaux, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Taboada, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_15320626_v23_n14_p1665_Garbervetsky
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Java real-time
quantitative memory requirements
scoped-memory
static analysis
Aircraft collisions
Analysis techniques
Closed form
Compile time
Dynamic memory
Free memory
Garbage collectors
Java real-time
Memory organizations
Memory requirements
Memory usage
Object-oriented languages
Program variables
Real time performance
Real-time specification for javas
scoped-memory
Semi-automatics
Space analysis
Upper Bound
Aircraft accidents
Automatic programming
Java programming language
Static analysis
Time series analysis
spellingShingle Java real-time
quantitative memory requirements
scoped-memory
static analysis
Aircraft collisions
Analysis techniques
Closed form
Compile time
Dynamic memory
Free memory
Garbage collectors
Java real-time
Memory organizations
Memory requirements
Memory usage
Object-oriented languages
Program variables
Real time performance
Real-time specification for javas
scoped-memory
Semi-automatics
Space analysis
Upper Bound
Aircraft accidents
Automatic programming
Java programming language
Static analysis
Time series analysis
Garbervetsky, D.
Yovine, S.
Braberman, V.
Rouaux, M.
Taboada, A.
Quantitative dynamic-memory analysis for Java
topic_facet Java real-time
quantitative memory requirements
scoped-memory
static analysis
Aircraft collisions
Analysis techniques
Closed form
Compile time
Dynamic memory
Free memory
Garbage collectors
Java real-time
Memory organizations
Memory requirements
Memory usage
Object-oriented languages
Program variables
Real time performance
Real-time specification for javas
scoped-memory
Semi-automatics
Space analysis
Upper Bound
Aircraft accidents
Automatic programming
Java programming language
Static analysis
Time series analysis
description Space- and time-predictability are hard to achieve for object-oriented languages with automated dynamic-memory management. Although there has been significant work to design APIs, such as the Real-Time Specification for Java (RTSJ), and to implement garbage collectors to enable real-time performance, quantitative space analysis is still in its infancy. This work presents the integration of a series of compile-time analysis techniques to help predicting quantitative memory usage. In particular, we focus on providing tool assistance for identifying RTSJ scoped-memory regions, their sizes, and overall memory usage. First, the tool-suite synthesizes a memory organization where regions are associated with methods. Second, it infers their sizes in parametric closed form in terms of relevant program variables. Third, it exhibits a parametric upper bound on the amount of available free memory required to execute a method. The experiments carried out with a RTSJ benchmark, a real-time aircraft collision detector, show that semi-automatic, tool-assisted generation of scoped-based code is both helpful and doable. © 2010 John Wiley & Sons, Ltd.
format JOUR
author Garbervetsky, D.
Yovine, S.
Braberman, V.
Rouaux, M.
Taboada, A.
author_facet Garbervetsky, D.
Yovine, S.
Braberman, V.
Rouaux, M.
Taboada, A.
author_sort Garbervetsky, D.
title Quantitative dynamic-memory analysis for Java
title_short Quantitative dynamic-memory analysis for Java
title_full Quantitative dynamic-memory analysis for Java
title_fullStr Quantitative dynamic-memory analysis for Java
title_full_unstemmed Quantitative dynamic-memory analysis for Java
title_sort quantitative dynamic-memory analysis for java
url http://hdl.handle.net/20.500.12110/paper_15320626_v23_n14_p1665_Garbervetsky
work_keys_str_mv AT garbervetskyd quantitativedynamicmemoryanalysisforjava
AT yovines quantitativedynamicmemoryanalysisforjava
AT brabermanv quantitativedynamicmemoryanalysisforjava
AT rouauxm quantitativedynamicmemoryanalysisforjava
AT taboadaa quantitativedynamicmemoryanalysisforjava
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