通过高效的基准生成改进Java垃圾收集的测试

A. O. Portillo-Dominguez, Vanessa Ayala-Rivera
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引用次数: 1

摘要

垃圾收集(GC)是多种现代技术(如Java、Android)的核心特性。一方面,与显式内存管理相比,它提供了显著的软件工程优势,比如防止大多数类型的内存泄漏。另一方面,GC是导致性能下降的一个已知原因。然而,要理解它对整个应用程序性能的确切影响是相当具有挑战性的。这是因为GC的不确定性使得正确地对其建模和评估其性能影响变得非常复杂。为了帮助解决这些问题,我们提供了一个引擎,通过有效地捕获实际Java应用程序所经历的GC/内存行为来生成真实的GC基准。通过全面的实验评估,我们还展示了这些基准如何有助于加强对gc相关进展的评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving the Testing of Java Garbage Collection Through an Efficient Benchmark Generation
Garbage Collection (GC) is a core feature of multiple modern technologies (e.g., Java, Android). On one hand, it offers significant software engineering benefits over explicitly memory management, like preventing most types of memory leaks. On the other hand, GC is a known cause of performance degradation. However, it is considerably challenging to understand its exact impact on the overall application performance. This is because the non-deterministic nature of GC makes very complex to properly model it and evaluate its performance impacts. To help tackling these problems, we present an engine to generate realistic GC benchmarks by enabling to effectively capture the GC/memory behaviours experienced by real-world Java applications. We also demonstrate, through a comprehensive experimental evaluation, how such benchmarks can be useful to strengthen the evaluation of GC-related advancements.
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