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Computer Science > Software Engineering

Title: Utilizing Deep Learning to Optimize Software Development Processes

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.
Subjects: Software Engineering (cs.SE); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)
DOI: 10.5281/zenodo.11004006
Report number: JCTAM-2024042100074
Cite as: arXiv:2404.13630 [cs.SE]
  (or arXiv:2404.13630v1 [cs.SE] for this version)

Submission history

From: Keqin Li [view email]
[v1] Sun, 21 Apr 2024 12:06:05 GMT (338kb)

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