Speeding Up Type-Specific Instrumentation for the Analysis of Complex Systems

Andrea Rosà, Walter Binder
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Abstract

Dynamic analysis is crucial for understanding and improving the performance of complex systems. Our work focuses on dynamic analyses on the Java Virtual Machine (JVM). Such analyses often rely on bytecode instrumentation to weave monitoring code into selected methods, so as to collect the desired metrics at runtime. Unfortunately, existing instrumentation frameworks offer limited capabilities. On the one hand, frameworks such as AspectJ that perform the weaving within the observed JVM cannot weave monitoring code within the Java class library, considerably limiting completeness of AspectJ-based analyses. On the other hand, frameworks such as DiSL that perform the weaving in a separate process offer full bytecode coverage, but cannot access certain reflective information that is available in AspectJ. Here, we present an extension of DiSL to expose reflective supertype information within the instrumentation process. This is challenging, because the observed application may make use of custom classloaders and the loaded classes are generally only known upon termination of the application. Our framework guarantees full bytecode coverage, while providing reflective supertype information. We show that our framework can significantly speed up dynamic analyses wrt. the current DiSL release.
加速用于复杂系统分析的特定类型仪器
动态分析对于理解和提高复杂系统的性能至关重要。我们的工作重点是对Java虚拟机(JVM)进行动态分析。这种分析通常依赖于字节码检测,将监视代码编织到选定的方法中,以便在运行时收集所需的指标。不幸的是,现有的工具框架提供的功能有限。一方面,在观察到的JVM中执行编织的AspectJ等框架不能在Java类库中编织监视代码,这极大地限制了基于AspectJ的分析的完整性。另一方面,在单独的进程中执行编织的框架(如DiSL)提供完整的字节码覆盖,但不能访问AspectJ中可用的某些反射信息。在这里,我们提供了DiSL的扩展,以在检测过程中公开反射超类型信息。这很有挑战性,因为观察到的应用程序可能使用自定义类加载器,而加载的类通常只有在应用程序终止时才知道。我们的框架保证完整的字节码覆盖,同时提供反射的超类型信息。我们展示了我们的框架可以显著加快动态分析的速度。当前的DiSL版本。
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