Lecture 20: Recursion Trees and the Master Method

Lecture 20: Recursion Trees and the Master Method

Recursion Trees

A recursion tree is useful for visualizing what happens when a recurrence is iterated. It diagrams the tree of recursive calls and the amount of work done at each call.

For instance, consider the recurrence

T(n) = 2T(n/2) + n².

The recursion tree for this recurrence has the following form:

In this case, it is straightforward to sum across each row of the tree to obtain the total work done at a given level:

This a geometric series, thus in the limit the sum is O(n²). The depth of the tree in this case does not really matter; the amount of work at each level is decreasing so quickly that the total is only a constant factor more than the root.

Recursion trees can be useful for gaining intuition about the closed form of a recurrence, but they are not a proof (and in fact it is easy to get the wrong answer with a recursion tree, as is the case with any method that includes ''...'' kinds of reasoning). As we saw last time, a good way of establishing a closed form for a recurrence is to make an educated guess and then prove by induction that your guess is indeed a solution. Recurrence trees can be a good method of guessing.

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