Foofah: A Programming-By-Example System for Synthesizing Data Transformation Programs
Summary: Programming-by-example system for synthesizing data transformation programs. Foofah requires only a small input-output example; it synthesizes a transformation program to automate real-world data wrangling tasks. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhongjun Jin (University of Michigan)
- 2. Michael R. Anderson (University of Michigan)
- 3. Michael Cafarella (University of Michigan)
- 4. H. V. Jagadish (University of Michigan)
BibTeX Citation
@inproceedings{jin_sigmod17,
title = {{Foofah: A Programming-By-Example System for Synthesizing Data Transformation Programs}},
author = {Jin, Zhongjun and Anderson, Michael R. and Cafarella, Michael and Jagadish, H. V.},
series = {{SIGMOD} '17},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3035918.3058732},
url = {https://dl.acm.org/doi/10.1145/3035918.3058732},
year = {2017}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,051 | Towards Benchmarking Feature Type Inference for AutoML Platforms | 2021 | SIGMOD | 6.385354e-05 |
| 6,928 | How do Categorical Duplicates Affect ML? A New Benchmark and Empirical Analyses | 2024 | VLDB | 5.7370426e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 94 | Potter's Wheel: An Interactive Data Cleaning System | 2001 | VLDB | 0.00034616103 |
| 1,165 | Foofah: Transforming Data By Example | 2017 | SIGMOD | 0.00011860616 |
| 3,547 | Learning Semantic String Transformations from Examples | 2012 | VLDB | 7.3225973e-05 |
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| 7 | 2,978 | Transform-Data-by-Example (TDE): An Extensible Search Engine for Data Transformations | 2018 | VLDB |
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