4 papers
Assessing the Impact of Code Changes on the Fault Localizability of Large Language Models
Sabaat Haroon, Ahmad Faraz Khan, Ahmad Humayun +5
Generative Large Language Models (LLMs) are increasingly used in non-generative software maintenance tasks, such as fault localization (FL). Success in FL depends on a models abili…
PRIVEE: Privacy-Preserving Vertical Federated Learning Against Feature Inference Attacks
Sindhuja Madabushi, Ahmad Faraz Khan, Haider Ali +6
Vertical Federated Learning (VFL) enables collaborative model training across organizations that share common user samples but hold disjoint feature spaces. Despite its potential,…
FLStore: Efficient Federated Learning Storage for non-training workloads
Ahmad Faraz Khan, Samuel Fountain, Ahmed M. Abdelmoniem +2
Federated Learning (FL) is an approach for privacy-preserving Machine Learning (ML), enabling model training across multiple clients without centralized data collection. With an ag…
LADs: Leveraging LLMs for AI-Driven DevOps
Ahmad Faraz Khan, Azal Ahmad Khan, Anas Mohamed +7
Automating cloud configuration and deployment remains a critical challenge due to evolving infrastructures, heterogeneous hardware, and fluctuating workloads. Existing solutions la…