Towards Selecting Informative Alternative Relational Query Plans for Database Education
Summary: Introduces TIPS, selecting k maximally informative alternative relational plans to expose optimizer trade-offs for database education, with batch and incremental variants. Provides hardness-aware approximation algorithms with guarantees, validated by learner feedback and a three-year classroom study. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Hui Li (Xidian University)
- 2. Hu Wang (Xidian University)
- 3. Sourav S. Bhowmick (Nanyang Technological University)
- 4. Zihao Ma (Xidian University)
BibTeX Citation
@inproceedings{li_sigmod26,
title = {{Towards Selecting Informative Alternative Relational Query Plans for Database Education}},
author = {Li, Hui and Wang, Hu and Bhowmick, Sourav S. and Ma, Zihao},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802122},
url = {https://dl.acm.org/doi/10.1145/3802122},
year = {2026}
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