The DOI matches its Crossref record.
Average Case Complete Problems
Abstract
Many interesting combinatorial problems were found to be NP-complete. Since there is little hope to solve them fast in the worst case, researchers look for algorithms which are fast just “on average”. This matter is sensitive to the choice of a particular NP-complete problem and a probability distribution of its instances. Some of these tasks were easy and some not. But one needs a way to distinguish the “difficult on average” problems. Such negative results could not only save “positive” efforts but may also be used in areas (like cryptography) where hardness of some problems is a frequent assumption. It is shown below that the Tiling problem with uniform distribution of instances has no polynomial “on average” algorithm, unless every NP-problem with every simple probability distribution has it. It is interesting to try to prove similar statements for other NP-problems which resisted so far “average case” attacks.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Analytic and Algorithmic Solution of Random Satisfiability Problems
Mézard, M., Parisi, G., & Zecchina, R. (2002) · Science · doi:10.1126/science.1073287 · Cited by 1,071
Quantum computational supremacy
Harrow, A. W., & Montanaro, A. (2017) · Nature · doi:10.1038/nature23458 · Cited by 702
Relations between average case complexity and approximation complexity
Feige, U. (2002) · Proceedings of the thiry-fourth annual ACM symposium on Theory of computing · doi:10.1145/509907.509985 · Cited by 351
Modern Cryptography, Probabilistic Proofs and Pseudorandomness
Goldreich, O. (1999) · Algorithms and Combinatorics · doi:10.1007/978-3-662-12521-2 · Cited by 265
One way functions and pseudorandom generators
Levin, L. A. (1987) · Combinatorica · doi:10.1007/bf02579323 · Cited by 257
Self-citation
Metadata
- Authors
- Levin, L. A.
- Venue
- SIAM Journal on Computing
- Published
- 1986-02
- Volume
- 15
- Issue
- 1
- Pages
- 285-286
- ISSN
- 0097-5397 (ISSN-L)
- 1095-7111
- OpenAlex
- W2100008268
- Cited by
- 424
- References
- 0
- FWCI
- 3.82
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Average Case Complete Problems. https://app.cochat.ai/papers/10.1137/0215020
- The paper
- Levin, L. A. (1986). Average Case Complete Problems. SIAM Journal on Computing. https://doi.org/10.1137/0215020
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.