LucidScript: Bottom-up Standardization for Data Preparation
Summary: Bottom-up standardization that treats a general-purpose data-prep script as a sketch of intent and rewrites it into a simpler, standardized, analyzable form. LucidScript implements this to improve readability, verification, and engineering/statistical hygiene. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Eugenie Lai (Massachusetts Institute of Technology)
- 2. Yuze Lou (University of Michigan)
- 3. Brit Youngmann (Technion)
- 4. Michael Cafarella (Massachusetts Institute of Technology)
BibTeX Citation
@article{lai_vldb24,
title = {{LucidScript: Bottom-up Standardization for Data Preparation}},
author = {Lai, Eugenie and Lou, Yuze and Youngmann, Brit and Cafarella, Michael},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4317--4320},
doi = {10.14778/3685800.3685864},
url = {https://doi.org/10.14778/3685800.3685864},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,744 | Auto-Suggest: Learning-to-Recommend Data Preparation Steps Using Data Science Notebooks | 2020 | SIGMOD | 8.1781662e-05 |
| 4,412 | Auto-Transform: Learning-to-Transform by Patterns | 2020 | VLDB | 6.7168614e-05 |
| 4,875 | Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search | 2021 | VLDB | 6.4689177e-05 |
| 6,250 | Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines | 2021 | CIDR | 5.9418015e-05 |
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