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

June 14, 2019 ยท The Ethereal ยท ๐Ÿ› 2013 IEEE International Symposium on Information Theory

๐Ÿ”ฎ THE ETHEREAL: The Ethereal
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Authors Yeow Meng Chee, Hui Zhang, Xiande Zhang arXiv ID 1906.06070 Category math.CO: Combinatorics Cross-listed cs.IT Citations 0 Venue 2013 IEEE International Symposium on Information Theory Last Checked 3 months ago
Abstract
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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