Distributed Spectrum-Based Fault Localization
Abstract
Spectrum-Based Fault Localization (SFL) is a popular approach for diagnosing faulty systems. SFL algorithms are inherently centralized, where observations are collected and analyzed by a single diagnoser. Applying SFL to diagnose distributed systems is challenging, especially when communication is costly and there are privacy concerns. We propose two SFL-based algorithms that are designed for distributed systems: one for diagnosing a single faulty component and one for diagnosing multiple faults. We analyze these algorithms theoretically and empirically. Our analysis shows that the distributed SFL algorithms we developed output identical diagnoses to centralized SFL while preserving privacy.
Cite
Text
Natan et al. "Distributed Spectrum-Based Fault Localization." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I5.25798Markdown
[Natan et al. "Distributed Spectrum-Based Fault Localization." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/natan2023aaai-distributed/) doi:10.1609/AAAI.V37I5.25798BibTeX
@inproceedings{natan2023aaai-distributed,
title = {{Distributed Spectrum-Based Fault Localization}},
author = {Natan, Avraham and Stern, Roni and Kalech, Meir},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2023},
pages = {6491-6498},
doi = {10.1609/AAAI.V37I5.25798},
url = {https://mlanthology.org/aaai/2023/natan2023aaai-distributed/}
}