4 papers
SieveFL: Hierarchical Runtime-Aware Pruning for Scalable LLM-Based Fault Localization
Mahdi Farzandway, Fatemeh Ghassemi
Automated fault localization requires connecting an observed test failure to the responsible method across thousands of candidates--a task that purely statistical approaches handle…
A Comprehensive Forecasting-Based Framework for Time Series Anomaly Detection: Benchmarking on the Numenta Anomaly Benchmark (NAB)
Mohammad Karami, Mostafa Jalali, Fatemeh Ghassemi
Time series anomaly detection is critical for modern digital infrastructures, yet existing methods lack systematic cross-domain evaluation. We present a comprehensive forecasting-b…
Automated Repair of C Programs Using Large Language Models
Mahdi Farzandway, Fatemeh Ghassemi
This study explores the potential of Large Language Models (LLMs) in automating the repair of C programs. We present a framework that integrates spectrum-based fault localization (…
OptiGradTrust: Byzantine-Robust Federated Learning with Multi-Feature Gradient Analysis and Reinforcement Learning-Based Trust Weighting
Mohammad Karami, Fatemeh Ghassemi, Hamed Kebriaei +1
Federated Learning (FL) enables collaborative model training across distributed medical institutions while preserving patient privacy, but remains vulnerable to Byzantine attacks a…