"我会被取代吗?评估 ChatGPT 对软件开发的影响以及程序员对人工智能工具的看法

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Mohammad Amin Kuhail , Sujith Samuel Mathew , Ashraf Khalil , Jose Berengueres , Syed Jawad Hussain Shah
{"title":"\"我会被取代吗?评估 ChatGPT 对软件开发的影响以及程序员对人工智能工具的看法","authors":"Mohammad Amin Kuhail ,&nbsp;Sujith Samuel Mathew ,&nbsp;Ashraf Khalil ,&nbsp;Jose Berengueres ,&nbsp;Syed Jawad Hussain Shah","doi":"10.1016/j.scico.2024.103111","DOIUrl":null,"url":null,"abstract":"<div><p>ChatGPT is a language model with artificial intelligence (AI) capabilities that has found utility across various sectors. Given its impact, we conducted two empirical studies to assess the potential and limitations of ChatGPT and other AI tools in software development. In the first study, we evaluated ChatGPT 3.5′s effectiveness in generating code for 180 coding problems from LeetCode, an online coding interview preparation platform. Our findings suggest that ChatGPT 3.5 is more effective in solving easy and medium coding problems but less reliable for harder problems. Further, ChatGPT 3.5 is somewhat more effective at coding problems with higher popularity scores. In the second study, we administered a questionnaire (<em>N</em> = 99) to programmers to gain insights into their views on ChatGPT and other AI tools. Our findings indicate that programmers use AI tools for various tasks, such as generating boilerplate code, explaining complex code, and conducting research. AI tools also help programmers to become more productive by creating better-performing, shorter, and more readable code, among other benefits. However, AI tools can sometimes misunderstand requirements and generate erroneous code. While most programmers are not currently concerned about AI tools replacing them, they are apprehensive about what the future may hold. Our research has also revealed associations between AI tool usage, trust, perceived productivity, and job security threats caused by the tools.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"235 ","pages":"Article 103111"},"PeriodicalIF":1.5000,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"“Will I be replaced?” Assessing ChatGPT's effect on software development and programmer perceptions of AI tools\",\"authors\":\"Mohammad Amin Kuhail ,&nbsp;Sujith Samuel Mathew ,&nbsp;Ashraf Khalil ,&nbsp;Jose Berengueres ,&nbsp;Syed Jawad Hussain Shah\",\"doi\":\"10.1016/j.scico.2024.103111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>ChatGPT is a language model with artificial intelligence (AI) capabilities that has found utility across various sectors. Given its impact, we conducted two empirical studies to assess the potential and limitations of ChatGPT and other AI tools in software development. In the first study, we evaluated ChatGPT 3.5′s effectiveness in generating code for 180 coding problems from LeetCode, an online coding interview preparation platform. Our findings suggest that ChatGPT 3.5 is more effective in solving easy and medium coding problems but less reliable for harder problems. Further, ChatGPT 3.5 is somewhat more effective at coding problems with higher popularity scores. In the second study, we administered a questionnaire (<em>N</em> = 99) to programmers to gain insights into their views on ChatGPT and other AI tools. Our findings indicate that programmers use AI tools for various tasks, such as generating boilerplate code, explaining complex code, and conducting research. AI tools also help programmers to become more productive by creating better-performing, shorter, and more readable code, among other benefits. However, AI tools can sometimes misunderstand requirements and generate erroneous code. While most programmers are not currently concerned about AI tools replacing them, they are apprehensive about what the future may hold. Our research has also revealed associations between AI tool usage, trust, perceived productivity, and job security threats caused by the tools.</p></div>\",\"PeriodicalId\":49561,\"journal\":{\"name\":\"Science of Computer Programming\",\"volume\":\"235 \",\"pages\":\"Article 103111\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science of Computer Programming\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167642324000340\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of Computer Programming","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167642324000340","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0

摘要

ChatGPT 是一种具有人工智能(AI)功能的语言模型,在各行各业都有应用。鉴于其影响力,我们进行了两项实证研究,以评估 ChatGPT 和其他人工智能工具在软件开发中的潜力和局限性。在第一项研究中,我们评估了 ChatGPT 3.5 为在线编码面试准备平台 LeetCode 的 180 个编码问题生成代码的有效性。我们的研究结果表明,ChatGPT 3.5 在解决简单和中等难度的编码问题时更有效,但在解决较难问题时则不太可靠。此外,ChatGPT 3.5 在解决受欢迎程度较高的问题时更有效。在第二项研究中,我们对程序员进行了问卷调查(N = 99),以了解他们对 ChatGPT 和其他人工智能工具的看法。我们的研究结果表明,程序员使用人工智能工具完成各种任务,如生成模板代码、解释复杂代码和进行研究。人工智能工具还能帮助程序员创建性能更好、更短、更易读的代码,从而提高工作效率。不过,人工智能工具有时也会误解需求,生成错误的代码。虽然大多数程序员目前并不担心人工智能工具会取代他们,但他们对未来可能出现的情况感到担忧。我们的研究还揭示了人工智能工具的使用、信任度、感知生产率和工具造成的工作安全威胁之间的关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
“Will I be replaced?” Assessing ChatGPT's effect on software development and programmer perceptions of AI tools

ChatGPT is a language model with artificial intelligence (AI) capabilities that has found utility across various sectors. Given its impact, we conducted two empirical studies to assess the potential and limitations of ChatGPT and other AI tools in software development. In the first study, we evaluated ChatGPT 3.5′s effectiveness in generating code for 180 coding problems from LeetCode, an online coding interview preparation platform. Our findings suggest that ChatGPT 3.5 is more effective in solving easy and medium coding problems but less reliable for harder problems. Further, ChatGPT 3.5 is somewhat more effective at coding problems with higher popularity scores. In the second study, we administered a questionnaire (N = 99) to programmers to gain insights into their views on ChatGPT and other AI tools. Our findings indicate that programmers use AI tools for various tasks, such as generating boilerplate code, explaining complex code, and conducting research. AI tools also help programmers to become more productive by creating better-performing, shorter, and more readable code, among other benefits. However, AI tools can sometimes misunderstand requirements and generate erroneous code. While most programmers are not currently concerned about AI tools replacing them, they are apprehensive about what the future may hold. Our research has also revealed associations between AI tool usage, trust, perceived productivity, and job security threats caused by the tools.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Science of Computer Programming
Science of Computer Programming 工程技术-计算机:软件工程
CiteScore
3.80
自引率
0.00%
发文量
76
审稿时长
67 days
期刊介绍: Science of Computer Programming is dedicated to the distribution of research results in the areas of software systems development, use and maintenance, including the software aspects of hardware design. The journal has a wide scope ranging from the many facets of methodological foundations to the details of technical issues andthe aspects of industrial practice. The subjects of interest to SCP cover the entire spectrum of methods for the entire life cycle of software systems, including • Requirements, specification, design, validation, verification, coding, testing, maintenance, metrics and renovation of software; • Design, implementation and evaluation of programming languages; • Programming environments, development tools, visualisation and animation; • Management of the development process; • Human factors in software, software for social interaction, software for social computing; • Cyber physical systems, and software for the interaction between the physical and the machine; • Software aspects of infrastructure services, system administration, and network management.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信