一种面向解释器的间接转移预测技术

解释器广泛应用于Java虚拟机、JavaScript执行引擎等托管运行环境中.解释器通常使用间接转移指令实现字节码分派.在现代多发射多级流水的微处理器中,间接转移预测失效严重制约解释器的性能.针对解释器提出了一种字节码指针引导的间接转移预测技术,其核心思想是使用解释器特有的字节码指针值区分不同的间接转移场景.该技术使用软硬件协同的方式,解释器中插入专门的引导指令以标记字节码指针,预测器在运行时刻使用字节码指针值预测转移目标地址.实验结果表明,该技术与常用的转移目标缓冲预测器相比,能提升Java解释器的性能达34.7％,能提升JavaScript解释器的性能达8.3％,与专用的硬件间接转移预测器TTC(tagged target cache)相比,也能提升Java解释器的性能达21.9％.     

针对SECD抽象机的基于踪迹的即时编译技术

为提高程序的整体执行效率,提出一种基于踪迹(trace-based)的通用即时编译技术。在SECD抽象机指令序列的解释执行中,将执行频率高的程序片段识别为踪迹,并编译成Java字节码,由Java虚拟机执行。任何用SECD抽象机实现的编程语言都可以使用该技术来提高程序执行效率。介绍该技术的实现方法,包括解释执行环境和Java字节码程序执行环境的转换方法,实现采用该技术的执行引擎框架。实验结果表明,该技术可有效提高程序的执行效率。     

A software tool for semi-automatic gridification of resource-intensive Java bytecodes and its application to ray tracing and sequence alignment

Computational Grids deliver the necessary computational infrastructure to perform resource-intensive computations such as the ones that solve the problems scientists are facing today. Exploiting Computational Grids comes at the expense of explicitly adapting the ordinary software implementing scientific problems to take advantage of Grid resources, which unavoidably requires knowledge on Grid programming. The recent notion of “gridifying” ordinary applications, which is based on semi-automatically deriving a Grid-aware version from the compiled code of a sequential application, promises users to be relieved from the requirement of manual usage of Grid APIs within their source codes. In this paper, we describe a novel gridification tool that allows users to easily parallelize Java applications on Grids. Extensive experiments with two real-world applications - ray tracing and sequence alignment - suggest that our approach provides a convenient balance between ease of gridification and Grid resource exploitation compared to manually using Grid APIs for gridifying ordinary applications.     

An empirical study of Java bytecode programs

We present a study of the static structure of real Java bytecode programs. A total of 1132 Java jar‐files were collected from the Internet and analyzed. In addition to simple counts (number of methods per class, number of bytecode instructions per method, etc.), structural metrics such as the complexity of control‐flow and inheritance graphs were computed. We believe this study will be valuable in the design of future programming languages and virtual machine instruction sets, as well as in the efficient implementation of compilers and other language processors. Copyright © 2006 John Wiley & Sons, Ltd.     

Decompilation of Java bytecode to Prolog by partial evaluation

Reasoning about Java bytecode (JBC) is complicated due to its unstructured control-flow, the use of three-address code combined with the use of an operand stack, etc. Therefore, many static analyzers and model checkers for JBC first convert the code into a higher-level representation. In contrast to traditional decompilation, such representation is often not Java source, but rather some intermediate language which is a good input for the subsequent phases of the tool. Interpretive decompilation consists in partially evaluating an interpreter for the compiled language (in this case JBC) written in a high-level language with respect to the code to be decompiled. There have been proofs-of-concept that interpretive decompilation is feasible, but there remain important open issues when it comes to decompile a real language such as JBC. This paper presents, to the best of our knowledge, the first modular scheme to enable interpretive decompilation of a realistic programming language to a high-level representation, namely of JBC to Prolog. We introduce two notions of optimality which together require that decompilation does not generate code more than once for each program point. We demonstrate the impact of our modular approach and optimality issues on a series of realistic benchmarks. Decompilation times and decompiled program sizes are linear with the size of the input bytecode program. This demonstrates empirically the scalability of modular decompilation of JBC by partial evaluation.     

一种使用CFT的Java卡内字节码校验算法

Java卡字节码校验是构成Java卡安全体系结构的重要组成部分.而传统的Java卡字节码校验由于Java智能卡资源的限制,无法在卡内进行.本文通过对控制流程图和类型推导的分析,提出了基于控制流程树的Java卡卡外翻译过程和卡内校验器算法,详细描述了CFT迁移机理并对于基于CFT的Java卡内字节码校验算法和可行性进行了分析与实践.     

一种新的Java智能卡上字节码校验算法

Java智能卡上的字节码校验是保障Java卡安全的重要手段。但是,由于Java智能卡本身的空间和运算器的限制,传统的字节码校验算法无法在Java智能卡上实现。为了解决此问题,本文在分析了现有方法的特点和不足的基础上提出了一种基于有向分枝图和缓存策略的字节码校验算法。效率分析和实践表明,该算法是一种可以在Java智能卡上实现
现的高效算法。     

Java程序调用流迷惑技术

提出了一种Java程序迷惑技术,将用户自定义类中的一些方法的代码提取出来,嵌入到对象池中的某个对象的方法中。由于所有位于对象池中的对象都被上溯到它们的基类型,方法多态使得只有在运行时刻才能真正确定到底哪个对象的方法被执行。从而能够显著隐藏程序的调用流程,有效防止静态分析。结合一些增强机制,在一定程度上可以抵御动态分析。实验结果显示,变换后的程序对性能影响很小。     

Flexible and efficient profiling with aspect‐oriented programming

Many profilers for virtual execution environments, such as the Java virtual machine (JVM), are implemented with low‐level bytecode instrumentation techniques, which is tedious, error‐prone, and complicates maintenance and extension of the tools. In order to reduce the development time and cost, we promote building profilers for the JVM using high‐level aspect‐oriented programming (AOP). We show that the use of aspects yields concise profilers that are easy to develop, extend, and maintain, because low‐level instrumentation details are hidden from the tool developer. In order to build efficient profilers, we introduce inter‐advice communication, an extension to common AOP languages that enables efficient data passing between advices that are woven into the same method using local variables. We illustrate our approach with two case studies. First, we show that an existing, instrumentation‐based tool for listener latency profiling can be easily recast as an aspect. Second, we present an aspect for comprehensive calling context profiling. In order to reduce profiling overhead, our aspect parallelizes application execution and profile creation, resulting in a speedup of 110% on a machine with more than two cores, compared with a primitive, non‐parallel approach. Copyright © 2011 John Wiley & Sons, Ltd.     

基于语义感知图神经网络的智能合约字节码漏洞检测方法

针对传统智能合约漏洞检测方法检测精度较低、误报率较高,以及基于神经网络的方法对字节码级智能合约特征挖掘不足的问题,提出了一种基于语义感知图神经网络的智能合约字节码漏洞检测方法.首先,以智能合约字节码划分基本块作为节点,并从字节码中提取基本块间的调用关系作为边,以此生成控制流图(control flow graph,CF...