arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2309.15768cs.SEcs.AI
收藏

人工智能在软件工程中的应用:案例研究与展望

AI in Software Engineering: Case Studies and Prospects

University of Western Australia(西澳大学)

Lei Wang

AI总结:

本文通过分析比较IBM Watson与Google AlphaGo两个案例,探讨AI技术在软件工程中的应用方式、智能决策差异及未来发展前景。

摘要:

人工智能(AI)与软件工程(SE)是计算机科学中的两个重要领域。近年来,研究人员试图将AI技术应用于软件开发的各个阶段,以提高软件产品的整体质量。此外,也有一些研究人员关注SE与AI的交叉领域。事实上,SE与AI之间的关系非常薄弱;然而,一个领域的方法和技术已被另一个领域采用。越来越多的软件产品能够像人类一样表现出智能行为。本文对使用不同AI技术解决现实世界挑战性问题的两个案例研究——IBM Watson和Google AlphaGo——进行了分析、评估和比较。基于对这两个案例研究的分析,在软件系统中使用深度学习和机器学习等AI技术有助于构建智能系统。Watson采用“决策支持”策略来帮助人类做出决策;而AlphaGo使用“自主决策”来选择有助于获得最佳结果的操作。此外,Watson从论文等人工资源中学习;另一方面,AlphaGo从照片等海量在线资源中学习。AlphaGo使用神经网络和强化学习来模拟人脑,这可能在医学研究中的诊断和治疗方面非常有用。然而,如果我们想在机器中复现人脑并将计算机视为思考者,仍有很长的路要走,因为人脑和机器在本质上是不同的。更有前景的方向是观察计算机和软件系统是否会变得越来越智能,以帮助解决人类无法完成的现实世界挑战性问题。

英文摘要:

Artificial intelligence (AI) and software engineering (SE) are two important areas in computer science. In recent years, researchers are trying to apply AI techniques in various stages of software development to improve the overall quality of software products. Moreover, there are also some researchers focus on the intersection between SE and AI. In fact, the relationship between SE and AI is very weak; however, methods and techniques in one area have been adopted in another area. More and more software products are capable of performing intelligent behaviour like human beings. In this paper, two cases studies which are IBM Watson and Google AlphaGo that use different AI techniques in solving real world challenging problems have been analysed, evaluated and compared. Based on the analysis of both case studies, using AI techniques such as deep learning and machine learning in software systems contributes to intelligent systems. Watson adopts 'decision making support' strategy to help human make decisions; whereas AlphaGo uses 'self-decision making' to choose operations that contribute to the best outcome. In addition, Watson learns from man-made resources such as paper; AlphaGo, on the other hand, learns from massive online resources such as photos. AlphaGo uses neural networks and reinforcement learning to mimic human brain, which might be very useful in medical research for diagnosis and treatment. However, there is still a long way to go if we want to reproduce human brain in machine and view computers as thinkers, because human brain and machines are intrinsically different. It would be more promising to see whether computers and software systems will become more and more intelligent to help with real world challenging problems that human beings cannot do.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑