Complete and Platform-Independent Calling Context Profiling for the Java Virtual Machine

Sarimbekov, Aibek; Moret, Philippe; Binder, Walter; Sewe, Andreas; Mezini, Mira

doi:10.1016/j.entcs.2011.11.006

Cited by 10 publications

(10 citation statements)

References 4 publications

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“…The solution proposed by Binder et al [5] in their ''JP'' tool was to statically instrument the .class files. They have reimplemented their tool, now called ''JP2'' [22], which is much more advanced and does not suffer from many of the restrictions the older version imposed. The new tool does not perform structural change on classes anymore but still has to statically modify the Thread class.…”

Section: Instrumenting Classes With a Java Agentmentioning

confidence: 99%

JBInsTrace: A tracer of Java and JRE classes at basic-block granularity by dynamically instrumenting bytecode

Caserta¹,

Zendra²

2014

Science of Computer Programming

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a b s t r a c tUnderstanding what happens during the runtime of a Java program is difficult. Tracking runtime flow can bring valuable information for program understanding and behavior analysis. Polymorphism, thread concurrency or even simple facts like the number of method invocations and the number of executed bytecodes are valuable information to track, but are difficult to compute outside the Java Virtual Machine (JVM) on running programs. In this paper, we present JBInsTrace, a new tool that instruments and traces Java bytecode. It produces static information about source code and a very fine grained trace of Java software execution, combining them to allow detailed analysis of the runtime. Our tool differs from others because it does not only trace program classes but also JRE classes, and does so at basic block level, without altering the JVM and without statically modifying class files. We explain JBInsTrace design, focused towards efficiency, which results in reasonable performance penalty.

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Section: Instrumenting Classes With a Java Agentmentioning

confidence: 99%

JBInsTrace: A tracer of Java and JRE classes at basic-block granularity by dynamically instrumenting bytecode

Caserta¹,

Zendra²

2014

Science of Computer Programming

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“…This feature provides a call-site-aware tracing [8] which allows the tracing of polymorphism in running programs. In fact, our technique provides enough information to re-simulate precisely the entire runtime flow of the profiled program and thus perform precise dynamic analyses.…”

Section: Fine-grained Tracementioning

confidence: 99%

A tracing technique using dynamic bytecode instrumentation of Java applications and libraries at basic block level

Caserta

Zendra

2011

Proceedings of the 6th Workshop on Implementation, Compilation, Optimization of Object-Oriented Languages, Programs and Systems

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Implementing a profiler to trace a program execution is nontrivial. One way to do this on running Java programs is through bytecode instrumentation. Nowadays, tools exist that ease the instrumentation process itself, but as far as we know, none offers an entirely dynamic implementation technique which is able to include the instrumentation of Java Runtime Environement (JRE) classes. In this paper we present the main principles of our technique, which performs such online bytecode instrumentation of both application and JRE classes, at basic block level.

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“…In this example, we assume an execution profiler that constructs calling-context trees, such as the one recently proposed by Sarimbekov et al [13]. A calling-context tree contains a node for each method call in each context, but it contains no duplicates in case the the same method is called in the same context multiple times.…”

Section: Execution Profilingmentioning

confidence: 99%

Continuation equivalence

Bodden

2011

Proceedings of the Ninth International Workshop on Dynamic Analysis

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Dynamic analyses reason about a program's concrete heap and control flow and hence can report on actual program behavior with high or even perfect accuracy. But many dynamic analyses require extensive program instrumentation, often slowing down the analyzed program considerably.In the past, researchers have hence developed specialized static optimizations that can prove instrumentation for a special analysis unnecessary at many program locations: the analysis can safely omit monitoring these locations, as their monitoring would not change the analysis results. Arguing about the correctness of such optimizations is hard, however, and ad-hoc approaches have lead to mistakes in the past.In this paper we present a correctness criterion called Continuation Equivalence, which allows researchers to prove static optimizations of dynamic analyses correct more easily. The criterion demands that an optimization may alter instrumentation at a program site only if the altered instrumentation produces a dynamic analysis configuration equivalent to the configuration of the un-altered program with respect to all possible continuations of the control flow.In previous work, we have used a notion of continuationequivalent states to prove the correctness of static optimization for finite-state runtime monitors. With this work, we propose to generalize the idea to general dynamic analyses.

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Complete and Platform-Independent Calling Context Profiling for the Java Virtual Machine

Cited by 10 publications

References 4 publications

JBInsTrace: A tracer of Java and JRE classes at basic-block granularity by dynamically instrumenting bytecode

JBInsTrace: A tracer of Java and JRE classes at basic-block granularity by dynamically instrumenting bytecode

A tracing technique using dynamic bytecode instrumentation of Java applications and libraries at basic block level

Continuation equivalence

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