Covering perfect hash families represent certain covering arrays compactly. Applying two probabilistic methods to covering perfect hash families improves upon the asymptotic upper bound for the minimum number of rows in a covering array with v symbols, k columns, and strength t. One bound can be realized by a randomized polynomial time construction algorithm using column resampling, while the other can be met by a deterministic polynomial time conditional expectation algorithm. Computational results are developed for both techniques. Further, a random extension algorithm further improves on the best known sizes for covering arrays in practice. An extensive set of computations with column resampling and random extension yields explicit constructions when k≤75\documentclass[12pt]{minimal}
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\begin{document}$$k \le 75$$\end{document} for strength seven, k≤200\documentclass[12pt]{minimal}
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\begin{document}$$k \le 200$$\end{document} for strength six, k≤600\documentclass[12pt]{minimal}
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\begin{document}$$k \le 600$$\end{document} for strength five, and k≤2500\documentclass[12pt]{minimal}
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\begin{document}$$k \le 2500$$\end{document} for strength four. When v>3\documentclass[12pt]{minimal}
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\begin{document}$$v > 3$$\end{document}, almost all known explicit constructions are improved upon. For strength t=3\documentclass[12pt]{minimal}
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\begin{document}$$t=3$$\end{document}, restrictions on the covering perfect hash family ensure the presence of redundant rows in the covering array, which can be removed. Using restrictions and random extension, computations for t=3\documentclass[12pt]{minimal}
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\begin{document}$$t=3$$\end{document} and k≤10,000\documentclass[12pt]{minimal}
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\begin{document}$$k \le 10{,}000$$\end{document} again improve upon known explicit constructions in the majority of cases. Computations for strengths three and four demonstrate that a conditional expectation algorithm can produce further improvements at the expense of a larger time and storage investment.
