Bytecode instrumentation is a valuable technique for transparently enhancing virtual execution environments for purposes such as monitoring or profiling. Current approaches to bytecode instrumentation either exclude some methods from instrumentation, severely restrict the ways certain methods may be instrumented, or require the use of native code. In this paper we compare different approaches to bytecode instrumentation in Java and come up with a novel instrumentation framework that goes beyond the aforementioned limitations. We evaluate our approach with an instrumentation for profiling which generates calling context trees of various platform-independent dynamic metrics.

SUMMARYVirtual execution environments, such as the Java Virtual Machine, promote platform-independent software development. However, when it comes to analyzing algorithm complexity and performance bottlenecks, available tools focus on platform-specific metrics, such as e.g. the CPU time consumption on a particular system. Other drawbacks of many prevailing profiling tools are high overhead, significant measurement perturbation, as well as reduced portability of profiling tools, which are often implemented in platformdependent native code. This article presents a novel profiling approach, which is entirely based on program transformation techniques, in order to build a profiling data structure that provides calling-contextsensitive program execution statistics. We explore the use of platform-independent profiling metrics, in order to make the instrumentation entirely portable and to generate reproducible profiles. We implemented these ideas within a Java-based profiling tool called JP. A significant novelty is that this tool achieves complete bytecode coverage, by statically instrumenting the core runtime libraries, and dynamically instrumenting the rest of the code. JP provides a small and flexible API to write customized profiling agents in pure Java, which are periodically activated to process the collected profiling information. Performance measurements point out that, despite the presence of dynamic instrumentation, JP causes significantly less overhead than a prevailing tool for the profiling of Java code.

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In this paper we introduce a novel scheme for portable CPU accounting and control in Java, which is based on program transformation techniques at the bytecode level and can be used with every standard Java Virtual Machine. In our approach applications, middleware, and the standard java runtime libraries (i.e., the Java Development Kit, or JDK) are modified in order to expose details regarding the execution of threads. This paper presents the details of how we reengineer Java bytecode for CPU management, including the strategies developed for transforming the JDK itself in a fully portable way.

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