Artificial Intelligence for Software Engineering: The Journey So Far and the Road Ahead

被引:0
作者
Ahmed, Iftekhar [1 ]
Aleti, Aldeida [2 ]
Cai, Haipeng [3 ]
Chatzigeorgiou, Alexander [4 ]
He, Pinjia [5 ]
Hu, Xing [6 ]
Pezze, Mauro [7 ,8 ,9 ]
Poshyvanyk, Denys [10 ]
Xia, Xin [11 ]
机构
[1] Univ Calif Irvine, Irvine, CA USA
[2] Monash Univ, Clayton, Australia
[3] SUNY Buffalo, Buffalo, NY USA
[4] Univ Macedonia, Thessaloniki, Greece
[5] Chinese Univ Hong Kong, Hong Kong, Peoples R China
[6] Zhejiang Univ, Hangzhou, Peoples R China
[7] Univ Svizzera Italiana, Lugano, Switzerland
[8] Univ Milano Bicocca, Milan, Italy
[9] Constructor Univ, Schaffhausen, Switzerland
[10] William & Mary, Williamsburg, VA USA
[11] Huawei Technol Co Ltd, Shenzhen, Peoples R China
关键词
Automated Software Development; Machine Learning; Large Language Models; Artificial Intelligence; Explainable AI; Ethical AI; JOBS;
D O I
10.1145/3719006
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Artificial intelligence and recent advances in deep learning architectures, including transformer networks and large language models, change the way people think and act to solve problems. Software engineering, as an increasingly complex process to design, develop, test, deploy, and maintain large-scale software systems for solving real-world challenges, is profoundly affected by many revolutionary artificial intelligence tools in general and machine learning in particular. In this roadmap for artificial intelligence in software engineering, we highlight the recent deep impact of artificial intelligence on software engineering by discussing successful stories of applications of artificial intelligence to classic and new software development challenges. We identify the new challenges that the software engineering community has to address in the coming years to successfully apply artificial intelligence in software engineering, and we share our research roadmap toward the effective use of artificial intelligence in the software engineering profession, while still protecting fundamental human values. We spotlight three main areas that challenge the research in software engineering: the use of generative artificial intelligence and large language models for engineering large software systems, the need of large and unbiased datasets and benchmarks for training and evaluating deep learning and large language models for software engineering, and the need of a new code of digital ethics to apply artificial intelligence in software engineering.
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页数:27
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