线性在共享分析中的作用

IF 0.4 4区计算机科学 Q4 COMPUTER SCIENCE, THEORY & METHODS

Mathematical Structures in Computer Science Pub Date : 2022-01-01 DOI:10.1017/S0960129522000160

G. Amato, M. Meo, F. Scozzari

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引用次数: 1

摘要

摘要共享分析用于静态地发现面向对象程序中可能重叠的数据结构。使用抽象解释框架，我们表明共享分析极大地受益于线性信息。当从变量开始的不同字段路径总是到达不同的对象时，变量在程序状态下是线性的。我们提出了一个基于图的抽象域，它可以表示混叠、线性和共享信息，并定义了分析类Java语言所需的所有抽象运算符。

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The role of linearity in sharing analysis

Abstract Sharing analysis is used to statically discover data structures which may overlap in object-oriented programs. Using the abstract interpretation framework, we show that sharing analysis greatly benefits from linearity information. A variable is linear in a program state when different field paths starting from it always reach different objects. We propose a graph-based abstract domain which can represent aliasing, linearity, and sharing information and define all the necessary abstract operators for the analysis of a Java-like language.

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来源期刊

Mathematical Structures in Computer Science 工程技术-计算机：理论方法

CiteScore

1.50

自引率

0.00%

发文量

审稿时长

12 months

期刊介绍： Mathematical Structures in Computer Science is a journal of theoretical computer science which focuses on the application of ideas from the structural side of mathematics and mathematical logic to computer science. The journal aims to bridge the gap between theoretical contributions and software design, publishing original papers of a high standard and broad surveys with original perspectives in all areas of computing, provided that ideas or results from logic, algebra, geometry, category theory or other areas of logic and mathematics form a basis for the work. The journal welcomes applications to computing based on the use of specific mathematical structures (e.g. topological and order-theoretic structures) as well as on proof-theoretic notions or results.