First, it is not always true in practice. A theoretical polynomial algorithm may have extremely large constant factors or exponents, thus rendering it impractical. For example, the problem of deciding whether a graph "G" contains "H" as a minor, where "H" is fixed, can be solved in a running time of "O"("n"2), where "n" is the number of vertices in "G". However, the big O notation hides a constant that depends superexponentially on "H". The constant is greater than formula_3 (using Knuth's up-arrow notation), and where "h" is the number of vertices in "H".