OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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of method parameters, local variables and items on the operand stack. An extended
version of this study was published in Concurrency and Computation: Practice and
Experience in 2003 [54]. The second study also considered the benchmarks in the Java
Grande Forum Benchmark Suite. It extended the first study by presenting techniques
for analyzing the data collected from dynamic profiling of Java applications. Finally,
the third study presented similar information for the benchmarks in the SPEC JVM98
Benchmark Suite.
Additional studies have been performed by other researchers examining the bytecodes
executed as Java applications execute. A study characterizing the bytecodes
and Ultra-SPARC machine code executed for the SPEC JVM98 Benchmark suite was
published by Radhakrishnan, Rubio and John in 1999 [95]. In 2001, Radhakrishnan
et. al. published an additional study which extended their previous work [96]. Herder
and Dujmovic also presented dynamic bytecode profile results in 2001 through the
release of a technical report [57].
3.4 Summary
This section has presented work relating to many different aspects of Java profiling
and optimization. Section 3.1 outlined other studies that consider modifying the
Java virtual machine instruction set in order to improve the performance of Java
applications. Many other optimization strategies have been developed which address
different types of inefficiencies present in the Java Virtual Machine. A collection
of these optimization techniques were presented in Section 3.2. Finally, Section 3.3
presented the efforts of other researchers to understand the behaviour of Java applications
through profiling. Tools that can be used to profile Java applications were
examined in addition to the results of previous profiling studies.