Error-Correcting Data Structures

dc.creatorde Wolf, Ronald
dc.date2008-02-11
dc.date2008-12-01
dc.date.accessioned2026-07-07T12:05:40Z
dc.date.available2026-07-07T12:05:40Z
dc.descriptionWe study data structures in the presence of adversarial noise. We want to encode a given object in a succinct data structure that enables us to efficiently answer specific queries about the object, even if the data structure has been corrupted by a constant fraction of errors. This new model is the common generalization of (static) data structures and locally decodable error-correcting codes. The main issue is the tradeoff between the space used by the data structure and the time (number of probes) needed to answer a query about the encoded object. We prove a number of upper and lower bounds on various natural error-correcting data structure problems. In particular, we show that the optimal length of error-correcting data structures for the Membership problem (where we want to store subsets of size s from a universe of size n) is closely related to the optimal length of locally decodable codes for s-bit strings.
dc.description15 pages LaTeX; an abridged version will appear in the Proceedings of the STACS 2009 conference
dc.identifierhttps://arxiv.org/abs/0802.1471
dc.identifierhttp://arxiv.org/abs/0802.1471
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/208436
dc.subjectData Structures and Algorithms
dc.titleError-Correcting Data Structures
dc.typetext

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