源代码理解任务的人工智能：系统的映射研究

IF 4.3 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information and Software Technology Pub Date : 2025-10-10 DOI:10.1016/j.infsof.2025.107915

Dzikri Rahadian Fudholi, Andrea Capiluppi

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引用次数: 0

摘要

背景：人工智能（AI）技术，特别是自然语言处理（NLP）和机器学习（ML），越来越多地用于支持源代码理解，这是软件工程中的一项基本活动。目的：这项系统的映射研究调查了这些技术是如何应用的，以四个研究问题（rq）为指导，重点关注任务类型，所使用的嵌入方法和预处理技术，所使用的机器学习模型以及现有的研究差距。方法：对227项同行评议的研究进行了回顾，确定了趋势，并提供了针对每个RQ的结构化映射。结果：研究结果揭示了深度学习的主要转变，特别是基于转换器和基于图形的模型，突出了未被探索的领域，如可解释性。结论：本研究提供了基于任务的分类，并为未来的人工智能源代码理解研究提供了见解和方向，为研究人员和实践者提供了支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Artificial intelligence for source code understanding tasks: A systematic mapping study

Context:

Artificial intelligence (AI) techniques, particularly natural language processing (NLP) and machine learning (ML), are increasingly used to support source code understanding, an essential activity in software engineering.

Objective:

This systematic mapping study investigates how these techniques are applied, guided by four Research Questions (RQs) focusing on the types of tasks, embedding methods & preprocessing techniques used, machine learning models employed, and existing research gaps.

Methods:

A review of 227 peer-reviewed studies identifies trends and provides a structured mapping addressing each RQ.

Results:

The findings reveal a dominant shift toward deep learning, especially transformer-based and graph-based models, highlighting underexplored areas such as explainability.

Conclusion:

This study provides a task-based classification and offers insights and directions for future research in AI-enabled source code understanding, supporting both researchers and practitioners.

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来源期刊

Information and Software Technology 工程技术-计算机：软件工程

CiteScore

9.10

自引率

7.70%

发文量

164

审稿时长

9.6 weeks

期刊介绍： Information and Software Technology is the international archival journal focusing on research and experience that contributes to the improvement of software development practices. The journal''s scope includes methods and techniques to better engineer software and manage its development. Articles submitted for review should have a clear component of software engineering or address ways to improve the engineering and management of software development. Areas covered by the journal include: • Software management, quality and metrics, • Software processes, • Software architecture, modelling, specification, design and programming • Functional and non-functional software requirements • Software testing and verification & validation • Empirical studies of all aspects of engineering and managing software development Short Communications is a new section dedicated to short papers addressing new ideas, controversial opinions, "Negative" results and much more. Read the Guide for authors for more information. The journal encourages and welcomes submissions of systematic literature studies (reviews and maps) within the scope of the journal. Information and Software Technology is the premiere outlet for systematic literature studies in software engineering.