Error-Correcting Data Structures

Author Ronald de Wolf

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Ronald de Wolf

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Ronald de Wolf. Error-Correcting Data Structures. In 26th International Symposium on Theoretical Aspects of Computer Science. Leibniz International Proceedings in Informatics (LIPIcs), Volume 3, pp. 313-324, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


We 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 {\sc 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.
  • Data structures
  • Error-correcting codes
  • Locally decodable codes
  • Membership


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