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Quantitative dynamic-memory analysis for Java

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Názov: Quantitative dynamic-memory analysis for Java
Autori: Diego Garbervetsky, Sergio Yovine, Martín Rouaux, Alejandro Taboada
Prispievatelia: The Pennsylvania State University CiteSeerX Archives
Zdroj: http://publicaciones.dc.uba.ar/Publications/2010/GYBRT10/Garbervestky_et_al.pdf.
Rok vydania: 2009
Zbierka: CiteSeerX
Popis: 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 closedform 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.
Druh dokumentu: text
Popis súboru: application/pdf
Jazyk: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.175.9907; http://publicaciones.dc.uba.ar/Publications/2010/GYBRT10/Garbervestky_et_al.pdf
Dostupnosť: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.175.9907
http://publicaciones.dc.uba.ar/Publications/2010/GYBRT10/Garbervestky_et_al.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Prístupové číslo: edsbas.1A39A6E3
Databáza: BASE
Popis
Abstrakt: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 closedform 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.