The time and space complexity of a problem \(X\) are measured in terms of the worst case time and space complexity of the asymptotically most efficient algorithm for deciding \(X\). In particular, we say that \(X\) has time complexity \(O(t(n))\) if the worst case time complexity of the most time efficient machine \(M\) deciding \(X\) is in \(O(t(n))\). Similarly, \(Y\) is said to be harder to decide (or more complex) than \(X\) if the time complexity of \(X\) is asymptotically bounded by the time complexity of \(Y\). The space complexity of a problem is defined similarly.