Etienne M. Gagnon

Soot: a Java bytecode optimization framework

This paper presents Soot, a framework for optimizing Java* bytecode. The framework is implemented in Java and supports three intermediate representations for representing Java bytecode: Baf, a streamlined representation of bytecode which is simple to manipulate; Jimple, a typed 3-address intermediate representation suitable for optimization; and Grimp, an aggregated version of Jimple suitable for decompilation. We describe the motivation for each representation, and the salient points in translating from one representation to another. In order to demonstrate the usefulness of the framework, we have implemented intraprocedural and whole program optimizations. To show that whole program bytecode optimization can give performance improvements, we provide experimental results for 12 large benchmarks, including 8 SPECjvm98 benchmarks running on JDK 1.2 for GNU/Linuxtm. These results show up to 8% improvement when the optimized bytecode is run using the interpreter and up to 21% when run using the JIT compiler.

Optimizing Java Bytecode Using the Soot Framework: Is It Feasible?

This paper presents Soot, a framework for optimizing Java™ bytecode. The framework is implementedin Java and supports three intermediate representations for representing Java bytecode: Baf, a streamlined representation of Javas stack-based bytecode; Jimple, a typed three-address intermediate representation suitable for optimization; and Grimp, an aggregated version of Jimple. Our approach to class file optimization is to first convert the stack-based bytecode into Jimple, a three-address form more amenable to traditional program optimization, and then convert the optimized Jimple back to bytecode. In order to demonstrate that our approach is feasible, we present experimental results showing the effects of processing class files through our framework. In particular, we study the techniques necessary to effectively translate Jimple back to bytecode, without losing performance. Finally, we demonstrate that class file optimization can be quite effective by showing the results of some basic optimizations using our framework. Our experiments were done on ten benchmarks, including seven SPECjvm98 benchmarks, and were executedon five different Java virtual machine implementations.

Practical virtual method call resolution for Java

This paper addresses the problem of resolving virtual method and interface calls in Java bytecode. The main focus is on a new practical technique that can be used to analyze large applications. Our fundamental design goal was to develop a technique that can be solved with only one iteration, and thus scales linearly with the size of the program, while at the same time providing more accurate results than two popular existing linear techniques, class hierarchy analysis and rapid type analysis.We present two variations of our new technique, variable-type analysis and a coarser-grain version called declared-type analysis. Both of these analyses are inexpensive, easy to implement, and our experimental results show that they scale linearly in the size of the program.We have implemented our new analyses using the Soot frame-work, and we report on empirical results for seven benchmarks. We have used our techniques to build accurate call graphs for complete applications (including libraries) and we show that compared to a conservative call graph built using class hierarchy analysis, our new variable-type analysis can remove a significant number of nodes (methods) and call edges. Further, our results show that we can improve upon the compression obtained using rapid type analysis.We also provide dynamic measurements of monomorphic call sites, focusing on the benchmark code excluding libraries. We demonstrate that when considering only the benchmark code, both rapid type analysis and our new declared-type analysis do not add much precision over class hierarchy analysis. However, our finer-grained variable-type analysis does resolve significantly more call sites, particularly for programs with more complex uses of objects.

SableCC, an object-oriented compiler framework

In this paper, we introduce SableCC, an object-oriented framework that generates compilers (and interpreters) in the Java programming language. This framework is based on two fundamental design decisions. Firstly, the framework uses object-oriented techniques to automatically build a strictly-typed abstract syntax tree that matches the grammar of the compiled language which simplifies debugging. Secondly, the framework generates tree-walker classes using an extended version of the visitor design pattern which enables the implementation of actions on the nodes of the abstract syntax tree using inheritance. These two design decisions lead to a tool that supports a shorter development cycle for constructing compilers. To demonstrate the simplicity of the framework, we present all the steps of building an interpreter for a mini-BASIC language. This example could be easily modified to provide on embedded scripting language in an application. We also provide a brief description of larger systems that have been implemented using the SableCC tool. We conclude that the use of object-oriented techniques significantly reduces the length of the programmer written code, can shorten the development time and finally, makes the code easier to read and maintain.

Efficient Inference of Static Types for Java Bytecode

In this paper, we present an efficient and practical algorithm for inferring static types for local variables in a 3-address, stackless, representation of Java bytecode.

Effective inline-threaded interpretation of Java bytecode using preparation sequences

Inline-threaded interpretation is a recent technique that improves performance by eliminating dispatch overhead within basic blocks for interpreters written in C [11]. The dynamic class loading, lazy class initialization, and multi-threading features of Java reduce the effectiveness of a straight-forward implementation of this technique within Java interpreters. In this paper, we introduce preparation sequences, a new technique that solves the particular challenge of effectively inline-threading Java. We have implemented our technique in the SableVM Java virtual machine, and our experimental results show that using our technique, inline-threaded interpretation of Java, on a set of benchmarks, achieves a speedup ranging from 1.20 to 2.41 over switch-based interpretation, and a speedup ranging from 1.15 to 2.14 over direct-threaded interpretation.

Relative factors in performance analysis of Java virtual machines

Many new Java runtime optimizations report relatively small, single-digit performance improvements. On modern virtual and actual hardware, however, the performance impact of an optimization can be influenced by a variety of factors in the underlying systems. Using a case study of a new garbage collection optimization in two different Java virtual machines, we show the relative effects of issues that must be taken into consideration when claiming an improvement. We examine the specific and overall performance changes due to our optimization and show how unintended side-effects can contribute to, and distort the final assessment. Our experience shows that VM and hardware concerns can generate variances of up to 9.5% in whole program execution time. Consideration of these confounding effects is critical to a good, objective understanding of Java performance and optimization.