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Full Description
This book constitutes the proceedings of the 34th International Conference on Software and Data Engineering, SEDE 2025, held in New Orleans, LA, USA, during October 20-21, 2025.
The 26 full papers presented in these proceedings were carefully reviewed and selected from 42 submissions. These papers focus on a wide range of topics within Software and Data Engineering and are categorized into the following topical sections: Software Engineering and Data Science & Artificial Intelligence.
Contents
.- Software Engineering and Data Science.
.- Drone Simulation in Precision Agriculture Using Unity.
.- Leveraging Generative AI for Proactive Security and Automated Remediation in Cloud-Native CI/CD Pipelines.
.- Optimizing Healthcare Pipelines for patient Benefit: A Data Engineering Perspectives on Preau-thorization Delays and Denials.
.- Pairwise Clustering on Numerical Datasets by Translation.
.- A Customizable Ad-hoc Java Client that Works with Bare Webservers.
.- DuckDB-Powered Geo-Spatial Analytics for hit-and-run Incidents: A Case Study on Montgom-ery County, Maryland, Open Data.
.- Analysis of Programming Capability of LLMs in the Context of Computer Science.
.- Predicting Early Breast Cancer Recurrence with Machine Learning.
.- Structural and Connectivity Patterns in the Maven Central Software Dependency Network.
.- Cloud-Native Generative AI for Automated Planogram Synthesis: A Diffusion Model Approach for Multi-Store Retail Optimization.
.- Applications Of Positive Unlabeled Learning in the field of DDoS attacks.
.- Robust Intrusion Detection in IoV Using PU Learning and Supervised Ensembles with Synthetic Data Augmentation on CICIoV2024.
.- The Potential of Large Language Models in Automating Software Testing: From Generation to Reporting.
.- Design and Evaluation of a Scalable Data Pipeline for AI-Driven Air Quality Monitoring in Low-Resource Settings.
.- Hybrid Taint Analysis for React: Automated XSS Prevention.
.- Artificial Intelligence.
.- Edge-Based Learning for Improved Classification Under Adversarial Noise.
.- Prompt-Driven Test Generation: Leveraging Large Language Models and Knowledge Graphs for Quality Assurance in Data-Intensive Software System.
.- Adversarial Machine Learning for Robust Password Strength Estimation.
.- Mitigating Hallucination Risks in GenAI Compliance Advisory Systems for the Financial Industry.
.- Prosense - Defending Text Generation with Adversarial Feedbac.
.- Machine Learning-Based AES Key Recovery via Side-Channel Analysis on the ASCAD Dataset.
.- Hand Line Classification.
.- Beyond Accuracy: Evaluating LLMs for validating community service provider directory.
.- Trustworthy Design Patterns for Multi-Agent Software Systems.
.- Designing Interpretable AI Models: Lightweight Parallelism for Real-Time Malware Detection & Prevention.
.- Interpretable AI with Lightweight Parallelism for Real-Time Auto Insurance Claims Triage.
