计算程序功能

Hessamaldin Mohammadi, Wided Ghardallou, R. Linger, A. Mili
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引用次数: 2

摘要

在软件工程中,从源代码的静态分析中提取程序的功能是一种有价值的能力,但它已被证明是一个难以实现的目标,主要是由于推导迭代语句的功能的困难。一些自动化工具通过展开线圈来消除这个困难;但这显然是一个不完美的解决方案,特别是考虑到循环占据了程序的大部分计算能力,是程序的大部分复杂性的所在地,也是程序的大部分错误的来源。在本文中,我们讨论了一个自动化工具的设计和正在进行的实现,该工具分三步推导程序的功能:首先,使用标准解析技术将源代码映射到抽象语法树(AST)上;然后将AST的每个节点映射到前后状态之间的方程;最后,将这些方程提交给一个符号计算引擎,该引擎将程序的最终状态作为初始状态的函数提取出来。循环函数是通过对语义识别器的模式匹配得到的,语义识别器捕获了必要的编程知识和领域知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computing Program Functions
Extracting the function of a program from a static analysis of its source code is a valuable capability in software engineering, but it has proved to be an elusive goal, due primarily to the difficulty of deriving the function of iterative statements. Several automated tools obviate this difficulty by unrolling the loops; but this is clearly an imperfect solution, especially in light of the fact that loops capture most of the computing power of a program, are the locus of most of its complexity, and the source of most of its faults. In this paper we discuss the design and ongoing implementation of an automated tool for deriving the function of a program in three steps: first, the source code is mapped onto an abstract syntax tree (AST), using standard parsing technology; then each node of the AST is mapped onto an equation between pre and post states; finally, these equations are submitted to a symbolic computation engine that extracts the final program state as a function of its initial state. Loop functions are derived by pattern matching against semantic recognizers, which capture the requisite programming knowledge and domain knowledge.
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