Module-Level Compile-Time Analysis for Industrial-Sized Software

工业规模软件的模块级编译时分析

• 批准号: 9804065
• 负责人: Barbara Ryder
• 金额: $ 5万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-09-01 至 2000-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9804065&HistoricalAwards=false
• 关键词: Module; Level; Compile; Time; Analysis

9804065 Software tools should have the choice of tunable, scalable, compile-time analyses, which provide adjustable levels of precision for predictable cost. New analysis techniques are needed to scale up to {\it industrial-sized} systems (i.e., 100,000 lines of code). Previous work seems conclusive: whole- program analysis does not scale suitably with a reasonable degree of precision for program transformation, data-flow-based testing applications, or program-understanding uses in certain circumstances. Thus, new techniques are needed. Program decomposition, uses a coarse-grained alias analysis of a C program to subdivide it into independently analyzable segments. Specific analyses, that vary in cost and precision, can be applied to different parts of a program. Initial experiments with this technique have enabled considerable gains in precision with modest increased cost for side-effect analysis of C programs. Research will focus on (i) development of techniques for selection of a specific analysis to apply to each program unit and (ii) empirical experimentation with these techniques using the PROLANGS Analysis Framework (PAF), a software platform for program analysis which currently includes flow- and context- sensitive side-effect and alias analysis for C programs.***

9804065软件工具应该有可调的，可扩展的，编译时分析的选择，提供可调的精度水平，可预测的成本。 需要新的分析技术来扩大到工业规模的系统（即， 100，000行代码）。以前的工作似乎是结论性的：对于程序转换、基于数据流的测试应用或在某些情况下的程序理解用途，整体程序分析不能以合理的精确度适当地缩放。 因此，需要新的技术。程序分解，使用C程序的粗粒度别名分析将其细分为可独立分析的段。 具体的分析，在成本和精度上各不相同，可以应用于程序的不同部分。使用这种技术的初步实验已经使C程序的副作用分析在精度上有了相当大的提高。 研究将侧重于（i）开发用于选择适用于每个程序单元的特定分析的技术，以及（ii）使用PROLANGS分析框架（PAF）对这些技术进行实证实验，PAF是一种用于程序分析的软件平台，目前包括对C程序的流和上下文敏感的副作用和别名分析。