IcedTea: Efficient and Responsive Time-Travel Debugging in Dataflow Systems
Summary: IcedTea: reverse time-travel debugging for distributed dataflow systems — periodically capture global operator states and allow rollback to any past interaction with stepwise replay. Formalizes the model and applies runtime/space optimizations to support responsive debugging of stateful, ML-heavy dataflows with low overhead. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Shengquan Ni (University of California Irvine)
- 2. Yicong Huang (University of California Irvine)
- 3. Zuozhi Wang (University of California Irvine)
- 4. Chen Li (University of California Irvine)
BibTeX Citation
@article{ni_vldb25,
title = {{IcedTea: Efficient and Responsive Time-Travel Debugging in Dataflow Systems}},
author = {Ni, Shengquan and Huang, Yicong and Wang, Zuozhi and Li, Chen},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {3},
pages = {902--914},
doi = {10.14778/3712221.3712251},
url = {https://doi.org/10.14778/3712221.3712251},
year = {2025}
}
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,066 | ML-Asset Management: Curation, Discovery, and Utilization | 2025 | VLDB | 5.093636e-05 |
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