SDEcho: Efficient Explanation of Aggregated Sequence Difference
Summary: SDEcho automates finding causes of differences between SQL-derived aggregated sequences, emphasizing sequence-level patterns, order, and dimensional contributors. It uses hybrid pruning across pattern, order, and dimension (and their interactions) to compactly prune the explanation space for accurate, scalable explanations. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Fei Ye (Fudan University)
- 2. Zikang Liu (Fudan University)
- 3. Xi Zhang (Fudan University)
- 4. Yinan Jing (Fudan University)
- 5. Zhenying He (Fudan University)
- 6. Yuxin Che (Fudan University)
- 7. Haoran Xiong (Fudan University)
- 8. Kai Zhang (Fudan University)
- 9. X. Sean Wang (Fudan University)
BibTeX Citation
@article{ye_vldb25,
title = {{SDEcho: Efficient Explanation of Aggregated Sequence Difference}},
author = {Ye, Fei and Liu, Zikang and Zhang, Xi and Jing, Yinan and He, Zhenying and Che, Yuxin and Xiong, Haoran and Zhang, Kai and Wang, X. Sean},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {3},
pages = {784--797},
doi = {10.14778/3712221.3712242},
url = {https://doi.org/10.14778/3712221.3712242},
year = {2025}
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