A Precise Framework for Source-Level Control-Flow Analysis

Idriss Riouak, Christoph Reichenbach, G. Hedin, Niklas Fors
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引用次数: 3

Abstract

This paper presents INTRACFG, a declarative and language-independent framework for constructing precise intraprocedural control-flow graphs (CFGs) based on the reference attribute grammar system JastAdd. Unlike most other frameworks, which build CFGs on an Intermediate Representation level, e.g., bytecode, our approach superimposes the CFGs on the Abstract Syntax Tree, enabling accurate client analysis. Moreover, INTRACFG overcomes expressivity limitations of an earlier RAG-based framework, allowing the construction of AST-Unrestricted CFGs: CFGs whose shape is not confined to the AST structure. We evaluate the expressivity of INTRACFG with INTRAJ, an application of INTRACFG to Java 7, by comparing two data flow analyses built on top of INTRAJ against tools from academia and from the industry. The results demonstrate that INTRAJ is effective at building precise and efficient CFGs and enables analyses with competitive performance.
源级控制流分析的精确框架
本文提出了一个基于引用属性语法系统JastAdd构建精确过程内控制流图(cfg)的声明性和语言无关框架。与其他大多数在中间表示层(例如字节码)上构建cfg的框架不同,我们的方法将cfg叠加在抽象语法树上,从而实现准确的客户端分析。此外,INTRACFG克服了早期基于rag的框架的表达性限制,允许构建AST- unrestricted CFGs:其形状不局限于AST结构的CFGs。我们用INTRAJ (INTRACFG在Java 7上的一个应用程序)来评估INTRACFG的表达能力,通过比较基于INTRAJ构建的两个数据流分析与学术界和工业界的工具。结果表明,INTRAJ可以有效地构建精确和高效的cfg,并使分析具有竞争力的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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