Sunkle Sagar, Saxena Krati, Patil Ashwini, Kulkarni Vinay
Tata Consultancy Services Research, Pune, 411013 India.
Softw Syst Model. 2022;21(3):1-23. doi: 10.1007/s10270-022-00982-6. Epub 2022 Feb 19.
Model-driven technologies (MD*), considered beneficial through abstraction and automation, have not enjoyed widespread adoption in the industry. In keeping with the recent trends, using AI techniques might help the benefits of MD* outweigh their costs. Although the modeling community has started using AI techniques, it is, in our opinion, quite limited and requires a change in perspective. We provide such a perspective through five industrial case studies where we use AI techniques in different modeling activities. We discuss our experiences and lessons learned, in some cases evolving purely modeling solutions with AI techniques, and in others considering the AI aids from the beginning. We believe that these case studies can help the researchers and practitioners make sense of various artifacts and data available to them and use applicable AI techniques to enhance suitable modeling activities.
模型驱动技术（MD*）通过抽象和自动化被认为是有益的，但在行业中尚未得到广泛应用。与最近的趋势一致，使用人工智能技术可能有助于使MD*的益处超过其成本。尽管建模社区已经开始使用人工智能技术，但在我们看来，其应用相当有限，并且需要视角的转变。我们通过五个工业案例研究提供了这样一种视角，在这些案例中我们在不同的建模活动中使用了人工智能技术。我们讨论了我们的经验和教训，在某些情况下用人工智能技术改进纯粹的建模解决方案，而在其他情况下从一开始就考虑人工智能辅助。我们相信这些案例研究可以帮助研究人员和从业者理解他们可获得的各种工件和数据，并使用适用的人工智能技术来增强合适的建模活动。
