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Complexity of Dependencies in Bounded Domains, Armstrong Codes, and Generalizations
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Complexity of Dependencies in Bounded Domains, Armstrong Codes, and Generalizations

Yeow Meng Chee, Hui Zhang and Xiande Zhang
arXiv.org
Cornell University Library, arXiv.org
14/06/2019

Abstract

Codes Domains Lower bounds Relational data bases
The study of Armstrong codes is motivated by the problem of understanding complexities of dependencies in relational database systems, where attributes have bounded domains. A \((q,k,n)\)-Armstrong code is a \(q\)-ary code of length \(n\) with minimum Hamming distance \(n-k+1\), and for any set of \(k-1\) coordinates there exist two codewords that agree exactly there. Let \(f(q,k)\) be the maximum \(n\) for which such a code exists. In this paper, \(f(q,3)=3q-1\) is determined for all \(q\geq 5\) with three possible exceptions. This disproves a conjecture of Sali. Further, we introduce generalized Armstrong codes for branching, or \((s,t)\)-dependencies, construct several classes of optimal Armstrong codes and establish lower bounds for the maximum length \(n\) in this more general setting.

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