BugDoc: Algorithms to Debug Computational Processes
Summary: BugDoc: provenance-driven, iterative approach that automatically infers root causes and provides succinct explanations for failures in pipelines. Evaluates cost, precision, and recall against the state of the art, with reproducible data and software. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Raoni Lourenço (New York University)
- 2. Juliana Freire (New York University)
- 3. Dennis Shasha (New York University)
BibTeX Citation
@inproceedings{lourenco_sigmod20,
title = {{BugDoc: Algorithms to Debug Computational Processes}},
author = {Lourenço, Raoni and Freire, Juliana and Shasha, Dennis},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3389763},
url = {https://dl.acm.org/doi/10.1145/3318464.3389763},
year = {2020}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,921 | CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning | 2024 | SIGMOD | 5.6432616e-05 |
| 7,183 | DataPrism: Exposing Disconnect between Data and Systems | 2022 | SIGMOD | 5.5917354e-05 |
| 7,212 | Capturing and Querying Fine-grained Provenance of Preprocessing Pipelines in Data Science | 2021 | VLDB | 5.5840773e-05 |
| 9,599 | BugDoc: A System for Debugging Computational Pipelines | 2020 | SIGMOD | 5.1549025e-05 |
| 10,855 | PipeLens: Identifying Interventions for Resolving Malfunctioning Data Science Pipelines | 2026 | VLDB | 4.9793485e-05 |
| 11,515 | Counterfactual Explanation at Will, with Zero Privacy Leakage | 2024 | SIGMOD | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,855 | PipeLens: Identifying Interventions for Resolving Malfunctioning Data Science Pipelines | 2026 | VLDB |
| 2 | 4,801 | Improving Reproducibility of Data Science Pipelines through Transparent Provenance Capture | 2020 | VLDB |
| 3 | 11,671 | Reconstructing and Querying ML Pipeline Intermediates | 2023 | CIDR |
| 4 | 13,598 | PROXAI: Interactive Provenance-Aware Debugging of Machine Learning Pipelines | 2026 | VLDB |
| 5 | 9,675 | Debugging Large-Scale Data Science Pipelines using Dagger | 2020 | VLDB |
| 6 | 8,302 | Fixed It For You: Protocol Repair Using Lineage Graphs | 2019 | CIDR |
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| 8 | 8,615 | A Demonstration of DLBD: Database Logic Bug Detection System | 2023 | VLDB |
| 9 | 8,517 | Causality-Guided Adaptive Interventional Debugging | 2020 | SIGMOD |
| 10 | 9,599 | BugDoc: A System for Debugging Computational Pipelines | 2020 | SIGMOD |