Use Cases of Program Task using Tools based on Machine Learning and Deep Learning

Use Cases of Program Task using Tools based on Machine Learning and Deep Learning

The difference of this paper is that it analyzes the latest machine learning and deep learning tools for various tasks of program such as program search, understanding, completion, and review. In addition, the purpose of this study is to increase the understanding of various tasks of program by examining specific cases of applying various tasks of program based on tools. Recently, machine learning (ML) and deep learning (DL) technologies have contributed to automation and improvement of efficiency in various software development tasks such as program search, understanding, completion, and review. This study examines the characteristics of the latest ML and DL tools implemented for various tasks of program. Although these tools have many strengths, they still have weaknesses in generalization in various programming languages and program structures, and efficiency of computational resources. In this study, we evaluated the characteristics of these tools in a real environment.