# Utilizing Deep Learning to Optimize Software Development Processes

arXiv: https://arxiv.org/abs/2404.13630 · HTML: https://mlsanity.com/paper/2404.13630/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 29 references that are in the map.
- First posted on arXiv 21 Apr 2024.

## Builds on (most cited first, 14 of 14)

- [NDC-Scene: Boost Monocular 3D Semantic Scene Completion in Normalized Device Coordinates Space](https://mlsanity.com/paper/2309.14616/) (2023)
- [Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review](https://mlsanity.com/paper/2402.10350/) (2024)
- [Improving Depth Gradient Continuity in Transformers: A Comparative Study on Monocular Depth Estimation with CNN](https://mlsanity.com/paper/2308.08333/) (2023)
- [DDN-SLAM: Real-time Dense Dynamic Neural Implicit SLAM](https://mlsanity.com/paper/2401.01545/) (2024)
- [Particle Filter SLAM for Vehicle Localization](https://mlsanity.com/paper/2402.07429/) (2024)
- [News Recommendation with Attention Mechanism](https://mlsanity.com/paper/2402.07422/) (2024)
- [Rumor Detection with a novel graph neural network approach](https://mlsanity.com/paper/2403.16206/) (2024)
- [Building Lane-Level Maps from Aerial Images](https://mlsanity.com/paper/2312.13449/) (2023)
- [Image Captioning in news report scenario](https://mlsanity.com/paper/2403.16209/) (2024)
- [Jointly Learning Selection Matrices For Transmitters, Receivers And Fourier Coefficients In Multichannel Imaging](https://mlsanity.com/paper/2402.19023/) (2024)
- [Optimization of Pressure Management Strategies for Geological CO2 Sequestration Using Surrogate Model-based Reinforcement Learning](https://mlsanity.com/paper/2403.07360/) (2024)
- [Research on emotionally intelligent dialogue generation based on automatic dialogue system](https://mlsanity.com/paper/2404.11447/) (2024)
- [Physics-informed Convolutional Recurrent Surrogate Model for Reservoir Simulation with Well Controls](https://mlsanity.com/paper/2305.09056/) (2023)
- [Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls](https://mlsanity.com/paper/2310.06319/) (2023)

## Built on by (most cited first, 15 of 15)

- [Automatic News Generation and Fact-Checking System Based on Language Processing](https://mlsanity.com/paper/2405.10492/) (2024)
- [Enhance Image-to-Image Generation with LLaVA-generated Prompts](https://mlsanity.com/paper/2406.01956/) (2024)
- [Image anomaly detection and prediction scheme based on SSA optimized ResNet50-BiGRU model](https://mlsanity.com/paper/2406.13987/) (2024)
- [Efficiency optimization of large-scale language models based on deep learning in natural language processing tasks](https://mlsanity.com/paper/2405.11704/) (2024)
- [Predict Click-Through Rates with Deep Interest Network Model in E-commerce Advertising](https://mlsanity.com/paper/2406.10239/) (2024)
- [Advanced AI Framework for Enhanced Detection and Assessment of Abdominal Trauma: Integrating 3D Segmentation with 2D CNN and RNN Models](https://mlsanity.com/paper/2407.16165/) (2024)
- [Recording Brain Activity While Listening to Music Using Wearable EEG Devices Combined with Bidirectional Long Short-Term Memory Networks](https://mlsanity.com/paper/2408.12124/) (2024)
- [Advancements in Feature Extraction Recognition of Medical Imaging Systems Through Deep Learning Technique](https://mlsanity.com/paper/2406.18549/) (2024)
- [Deep Learning in Medical Image Classification from MRI-based Brain Tumor Images](https://mlsanity.com/paper/2408.00636/) (2024)
- [Comprehensive Overview of Artificial Intelligence Applications in Modern Industries](https://mlsanity.com/paper/2409.13059/) (2024)
- [Advanced Multimodal Deep Learning Architecture for Image-Text Matching](https://mlsanity.com/paper/2406.15306/) (2024)
- [Analysis and Design of a Personalized Recommendation System Based on a Dynamic User Interest Model](https://mlsanity.com/paper/2410.09923/) (2024)
- [Detecting and Classifying Defective Products in Images Using YOLO](https://mlsanity.com/paper/2412.16935/) (2024)
- [Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation](https://mlsanity.com/paper/2501.16692/) (2025)
- [Research on Edge Detection of LiDAR Images Based on Artificial Intelligence Technology](https://mlsanity.com/paper/2406.09773/) (2024)

## Abstract (arXiv)

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.