面向对象伪装的智能分析技术

Jeremy Singer, Gavin Brown, M. Luján, I. Watson
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引用次数: 18

摘要

对象伪装涉及在实例化时或实例化之前对长寿命对象的识别。它是分代垃圾收集系统的关键优化,分代垃圾收集系统是大多数高性能Java虚拟机的标准配置。这篇论文提出了一项新的研究,用于表明物体寿命的因素。我们采用归一化互信息的信息论度量来比较这些不同的因素在一个共同的框架内。对四个标准Java基准程序的垃圾收集跟踪的研究表明,其中一些因素(如分配位置和对象类型)高度依赖。我们还基于面向对象的度量来识别和度量新的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards intelligent analysis techniques for object pretenuring
Object pretenuring involves the identification of long-lived objects at or before their instantiation. It is a key optimization for generational garbage collection systems, which are standard in most high performance Java virtual machines. This paper presents a new study of factors that are used to indicate object lifespans. We adopt the information theory measurement of normalized mutual information to compare these various different factors in a common framework. A study of garbage collection traces from four standard Java benchmark programs shows that there is high dependence on some of these factors such as allocation site and object type. We also identify and measure new factors based on object-oriented metrics.
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