Relaxed Locally Correctable Codes with Nearly-Linear Block Length and Constant Query Complexity

Abstract

SIAM Journal on Computing, Volume 51, Issue 6, Page 1839-1865, December 2022.
Abstract. Locally correctable codes (LCCs) are error correcting codes [math] which admit local algorithms that correct any individual symbol of a corrupted codeword via a minuscule number of queries. For systematic codes, this notion is stronger than that of locally decodable codes (LDCs), where the goal is to only recover individual symbols of the message. One of the central problems in algorithmic coding theory is to construct [math]-query LCCs and LDCs with minimal block length. Alas, state-of-the-art of such codes requires super-polynomial block length to admit [math]-query algorithms for local correction and decoding, despite much attention during the last two decades. The study of relaxed LCCs and LDCs, which allow the correction algorithm to abort (but not err) on a small fraction of the locations, provides a way to circumvent this barrier. This relaxation turned out to allow constant-query correcting and decoding algorithms for codes with polynomial block length. Focusing on local correction, Gur, Ramnarayan, and Rothblum [Proceedings of the 9th Innovations in Theoretical Computer Science Conference, ITCS’18, 2018, pp. 1–27] showed that there exist [math]-query relaxed LCCs that achieve nearly-quartic block length [math], for an arbitrarily small constant [math]. We construct an [math]-query relaxed LCC with nearly-linear block length [math], for an arbitrarily small constant [math]. This significantly narrows the gap between the lower bound which states that there are no [math]-query relaxed LCCs with block length [math]. In particular, our construction matches the parameters achieved by Ben-Sasson et al. [SIAM J. Comput., 36 (2006), pp. 889–974], who constructed relaxed LDCs with the same parameters. This resolves an open problem raised by Gur, Ramnarayan, and Rothblum [Proceedings of the 9th Innovations in Theoretical Computer Science Conference, ITCS’18, 2018, pp. 1–27].