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Learning Algorithms for Automatic Data Structure Design

Summary: Learning-based search for automatic key-value data-structure design guided by workload specs, navigating a design space of ~10^100 possibilities. Outputs an abstract syntax tree for code generation, delivering near-optimal designs in seconds. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6070
Venue
SIGMOD
Year
2021
Pagerank
5.093636e-05
Overall Rank
11,643 | 20.12%
DOI
10.1145/3448016.3450570

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BibTeX Citation

@inproceedings{guo_sigmod21,
        title = {{Learning Algorithms for Automatic Data Structure Design}},
        author = {Guo, Demi},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3450570},
        url = {https://dl.acm.org/doi/10.1145/3448016.3450570},
        year = {2021}
}

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