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Fine-Grained Complexity Analysis of Queries: From Decision to Counting and Enumeration

Summary: Survey of fine-grained complexity for query answering that unifies decision, counting, and enumeration tasks, presenting algorithmic techniques, complexity measures and conditional lower bounds. Emphasizes consequences for aggregation and probabilistic databases, and enumeration trade-offs. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1833
Venue
PODS
Year
2020
Pagerank
5.3872753e-05
Overall Rank
8,673 | 40.50%
DOI
10.1145/3375395.3389130

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{durand_pods20,
        address = {New York, NY, USA},
        series = {{PODS} '20},
        title = {{Fine-Grained Complexity Analysis of Queries: From Decision to Counting and Enumeration}},
        url = {https://dl.acm.org/doi/10.1145/3375395.3389130},
        doi = {10.1145/3375395.3389130},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Durand, Arnaud},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,985 Change Propagation Without Joins 2023 VLDB 6.412102e-05
5,593 Beyond Equi-joins: Ranking, Enumeration and Factorization 2021 VLDB 6.1552328e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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