Permutation property testing under different metrics with low query complexity

Jacob Fox, Fan Wei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The goal of property testing is to quickly distinguish between objects which satisfy a property and objects that are far from satisfying the property. There are now several general results in this area which show that natural properties of combinatorial objects can be tested with constant" query complexity, depending only on and the property, and not on the size of the object being tested. The upper bound on the query complexity coming from the proof techniques are often enormous and impractical. It remains a major open problem if better bounds hold. Hoppen, Kohayakawa, Moreira, and Sampaio conjectured and Klimosova and Kral' proved that hereditary permutation properties are strongly testable, i.e., can be tested with respect to Kendall's tau distance. The query complexity bound coming from this proof is huge. Even for testing a single forbidden sub permutation it is of Ackermann-type in 1= We give a new proof which gives a polynomial bound in 1= for testing a single forbidden subpermutation. Maybe surprisingly, for testing with respect to the rectangular distance, we prove there is a universal (not depending on the property), polynomial in 1/ query complexity bound for two-sided testing hereditary properties of sufficiently large permutations. We further give a nearly linear bound with respect to a closely related metric which also depends on the smallest forbidden sub permutation for the property. Finally, we show that several different permutation metrics of interest are related to the rectangular distance, yielding similar results for testing with respect to these metrics.

Original languageEnglish (US)
Title of host publication28th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2017
EditorsPhilip N. Klein
PublisherAssociation for Computing Machinery
Pages1618-1637
Number of pages20
ISBN (Electronic)9781611974782
DOIs
StatePublished - 2017
Externally publishedYes
Event28th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2017 - Barcelona, Spain
Duration: Jan 16 2017Jan 19 2017

Publication series

NameProceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
Volume0

Other

Other28th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2017
Country/TerritorySpain
CityBarcelona
Period1/16/171/19/17

All Science Journal Classification (ASJC) codes

  • Software
  • General Mathematics

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