Utilizing Deep Learning to Optimize Software Development Processes

April 21, 2024 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Keqin Li, Armando Zhu, Peng Zhao, Jintong Song, Jiabei Liu arXiv ID 2404.13630 Category cs.SE: Software Engineering Cross-listed cs.AI, cs.CL, cs.LG Citations 31 Venue arXiv.org Last Checked 4 months ago
Abstract
This study explores the application of deep learning technologies in software development processes, particularly in automating code reviews, error prediction, and test generation to enhance code quality and development efficiency. Through a series of empirical studies, experimental groups using deep learning tools and control groups using traditional methods were compared in terms of code error rates and project completion times. The results demonstrated significant improvements in the experimental group, validating the effectiveness of deep learning technologies. The research also discusses potential optimization points, methodologies, and technical challenges of deep learning in software development, as well as how to integrate these technologies into existing software development workflows.
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