Software and Data Engineering

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.

. - 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.