preprint Open access

Utilizing Deep Learning to Optimize Software Development Processes

  • arXiv (Cornell University)
  • Cornell University
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Paper overview

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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Publication details

DOI
10.48550/arxiv.2404.13630
OpenAlex
W4395443958
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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