Automatic code generation has recently attracted large attention and is becoming more significant to the software development process. Solutions based on Machine Learning and Artificial Intelligence are being used to increase human and software efficiency in potent and innovative ways. In this paper, we aim to leverage these developments and introduce a novel approach to generating frontend component code for the popular Angular framework. We propose to do this using behavior-driven development test specifications as input to a transformer-based machine learning model. Our approach aims to drastically reduce the development time needed for web applications while potentially increasing software quality and introducing new research ideas toward automatic code generation.

翻译：自动代码生成近期引起了广泛关注，并在软件开发过程中日益凸显其重要性。基于机器学习与人工智能的解决方案正通过高效创新的方式提升人类与软件的效率。本文旨在利用这些进展，提出一种为流行Angular框架生成前端组件代码的新方法。我们提议以行为驱动开发测试规约作为输入，采用基于Transformer的机器学习模型来实现这一目标。我们的方法旨在大幅缩短Web应用的开发时间，同时可能提升软件质量，并为自动代码生成领域引入新的研究思路。