揭示开源VR软件中的代码克隆模式:一项实证研究

IF 3.1 2区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Huashan Chen, Zisheng Huang, Yifan Xu, Wenjie Huang, Xuheng Wang, Jinfu Chen, Haotang Li, Kebin Peng, Feng Liu, Sen He
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引用次数: 0

摘要

代码克隆在软件开发中经常出现,经常导致各种维护和安全问题。虽然对传统软件中的代码克隆进行了大量研究,但据我所知,对虚拟现实(VR)软件中的克隆进行的研究缺乏考虑到其独特性的研究,特别是与源代码一起存在大量序列化文件的研究。本文首次对345个开源VR项目中的软件克隆进行了大规模的定量实证分析,使用NiCad检测器进行源代码克隆检测,使用大型语言模型(llm)识别序列化的文件克隆。在七个精心制定的研究问题的指导下,我们的研究导致了对VR软件中的克隆现象的一些见解。这些发现及其意义有望为VR领域的研究人员和软件开发人员提供有用的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Unveiling code clone patterns in open source VR software: an empirical study

Unveiling code clone patterns in open source VR software: an empirical study

Code cloning is frequently observed in software development, often leading to a variety of maintenance and security issues. While substantial research has been conducted on code cloning in traditional software, to the best of my knowledge, there is a lack of studies on cloning in virtual reality (VR) software that consider its unique nature, particularly the presence of numerous serialized files in conjunction with the source code. In this paper, we conduct the first large-scale quantitative empirical analysis of software clones in 345 open-source VR projects, using the NiCad detector for source code clone detection and large language models (LLMs) for identifying serialized file clones. Our study leads to a number of insights into cloning phenomena in VR software, guided by seven carefully formulated research questions. These findings, along with their implications, are anticipated to provide useful guidance for both researchers and software developers within the VR field.

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来源期刊
Automated Software Engineering
Automated Software Engineering 工程技术-计算机:软件工程
CiteScore
4.80
自引率
11.80%
发文量
51
审稿时长
>12 weeks
期刊介绍: This journal details research, tutorial papers, survey and accounts of significant industrial experience in the foundations, techniques, tools and applications of automated software engineering technology. This includes the study of techniques for constructing, understanding, adapting, and modeling software artifacts and processes. Coverage in Automated Software Engineering examines both automatic systems and collaborative systems as well as computational models of human software engineering activities. In addition, it presents knowledge representations and artificial intelligence techniques applicable to automated software engineering, and formal techniques that support or provide theoretical foundations. The journal also includes reviews of books, software, conferences and workshops.
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