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

9804065软件工具应该有可调的、可扩展的、编译时分析的选择，它为可预测的成本提供可调的精度水平。需要新的分析技术来扩展到工业规模的系统（例如，100,000行代码）。先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程序或在某些情况下的程序理解使用，整个程序分析不能适当地以合理的精度进行扩展。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部分。具体的分析，在成本和精度上有所不同，可以应用于程序的不同部分。使用该技术的初步实验使得C程序的副作用分析在精度上有了相当大的提高，而成本却适度增加。研究将集中在(i)开发用于选择特定分析的技术，以应用于每个程序单元；（ii）使用PROLANGS分析框架（PAF）对这些技术进行实证实验，这是一个程序分析的软件平台，目前包括流程和上下文敏感的副作用和C程序的别名分析

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.***