Static type inference method and system for Python external function

Abstract

The invention relates to a static type inference method and system for a Python external function. The method comprises the following steps: S1, performing language separation on a Python/C multi-language project; for a C language file obtained after separation, identifying external function declarations in the C language file, and analyzing parameter type conversion and return type conversion realized by an external function corresponding to each external function declaration; S2, carrying out type inference according to each external function declaration, the parameter type conversion, and the return type conversion, and carrying out parameter-free function declaration consistency check on each external function declaration and the corresponding external function. According to the method provided by the invention, the type signature of an external function can be inferred, and a Python static type inference tool in the prior art is enhanced, so that the Python static type inference tool can analyze external function calling in a program and check vulnerabilities that external function declarations are inconsistent with the implementation thereof.

Description

technical field [0001] The invention relates to the fields of programming language and static analysis, in particular to a static type inference method and system for Python external functions. Background technique [0002] Static type inference is one of the important means to maintain the security of dynamically typed language programs. However, foreign functions implemented in another programming language are often outside the scope of the host language's type inference. As a popular dynamically typed language, Python has a large number of widely used Python packages that are multi-language architectures that include C / C++ external extensions. [0003] Both academia and industry have made a lot of attempts on Python's static type inference. These jobs can be divided into the following three categories: [0004] 1. Support type annotation through extended syntax, and perform type inference based on type annotation. Representative ones include Mypy from the Python commu...

AI Technical Summary

Problems solved by technology

These works often use methods such as directly ignoring (such as treating as object type) or preset type stubs to deal with external objects, and the accuracy of type inference is not good or requires manual assistance.

[0007] It can be seen that the existing deterministic and non-type-based static type inference tools for Python cannot effectively handle external functions

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