# A Semi-Random Construction of Small Covering Arrays

## TL;DR

This paper introduces a semi-random method combining probabilistic and linear algebraic techniques to construct small covering arrays with improved upper bounds on their size, benefiting applications requiring efficient combinatorial designs.

## Contribution

It presents a novel semi-random construction that tightens upper bounds on covering array sizes by a factor of 
, especially for prime power symbol sets.

## Key findings

- Improved upper bounds on  for prime power v.
- Construction of arrays covering maximum subsets of size t.
- Method applicable to large v, not necessarily prime powers.

## Abstract

Given a set $S$ of $v \ge 2$ symbols, and integers $k \ge t \ge 2$ and $N \ge 1$, an $N \times k$ array $A \in S^{N \times k}$ is an $(N; t, k, v)$-covering array if all sequences in $S^t$ appear as rows in every $N \times t$ subarray of $A$. These arrays have a wide variety of applications, driving the search for small covering arrays. The covering array number, $\mathrm{CAN}(t,k,v)$, is the smallest $N$ for which an $(N; t,k,v)$-covering array exists. In this paper, we combine probabilistic and linear algebraic constructions to improve the upper bounds on $\mathrm{CAN}(t,k,v)$ by a factor of $\ln v$, showing that for prime powers $v$, $\mathrm{CAN}(t,k,v) \le (1 + o(1)) \left( (t-1) v^t / (2 \log_2 v - \log_2 (v+1)) \right)\log_2 k$, which also offers improvements for large $v$ that are not prime powers. Our main tool, which may be of independent interest, is a construction of an array with $v^t$ rows that covers the maximum possible number of subsets of size $t$.