为Python实现基于类型的抽象语义

IF 0.7 4区数学 Q3 COMPUTER SCIENCE, THEORY & METHODS

Journal of Logical and Algebraic Methods in Programming Pub Date : 2025-02-01 DOI:10.1016/j.jlamp.2024.101032

Andrei Nacu

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引用次数: 0

摘要

Python是一种强但动态类型的高级编程语言。在本文中，我们提出了一个类型推断框架，用于隔离地计算Python函数的规范。为了实现这一点，我们的目标是使用基于抽象解释的数据流分析来推断使用内置类型、操作符和函数的Python程序子集的变量类型。要计算在每个程序点中找到的表达式，需要对遇到的操作和函数进行说明。我们提出了一种从Typeshed项目中提取这些规范的方法，该项目包含一组用于内置和流行的第三方库的注释。然后将使用这些规范将所建议的类型推断扩展到大型Python程序。

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Towards a type-based abstract semantics for Python

Python is a high-level programming language that is strongly, but dynamically typed. In this paper, we propose a type inference framework to compute specifications for Python functions in isolation. To achieve this, we aim to use an abstract-interpretation-based data flow analysis to infer variable types on a subset of Python programs that use built-in types, operators and functions. To evaluate the expressions found in every program point, specifications for the encountered operations and functions are required. We propose a method for extracting these specifications from the Typeshed project, which contains a set of annotations for built-in and popular third-party libraries. These specifications will be used then to extend the proposed type inference to large Python programs.

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来源期刊

Journal of Logical and Algebraic Methods in Programming COMPUTER SCIENCE, THEORY & METHODS-LOGIC

CiteScore

2.60

自引率

22.20%

发文量

期刊介绍： The Journal of Logical and Algebraic Methods in Programming is an international journal whose aim is to publish high quality, original research papers, survey and review articles, tutorial expositions, and historical studies in the areas of logical and algebraic methods and techniques for guaranteeing correctness and performability of programs and in general of computing systems. All aspects will be covered, especially theory and foundations, implementation issues, and applications involving novel ideas.