CSC207.01 2014S, Class 28: Quicksort
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_Overview_

* Preliminaries.
    * Upcoming work.
    * Questions.
* A quick introduction to Quicksort.
* Key ideas from Quicksort.

Preliminaries
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### Upcoming Work

* Today's lab writeup: Exercise 4 (implement Partition)
* Reading for Monday: A List ADT and Array-based lists (forthcoming)
* NO HOMEWORK THIS WEEK!

### Admin

* Have fun with Earnest!
* EB is the note taker today.

Aspects of QuickSort
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* O(n log(n)) is best and average case
* O(n squared) is the worst case scenario (if the pivot is the first or last element each time)
* Still, generally faster than other O(n log(n)) algorithms

So what is the pivot?

* It's the point from which we divide and conquer

Is QuickSort stable?

* No, and the ways to make it stable are pretty darn inefficient.
  [Well, more complicated than inefficient.]

More importantly,  it's memory efficient.

* We don't have to make another array when sorting an array!
* This means it sorts in-place!

Practice:

Let's organize this array:

    [slots are numbered 0 – 11]
    lb = 0; ub = 12
    a|l|p|h|a|b|e|t|i|c|a|l [we pick b as our pivot]

    lb = 1; ub = 12
    b|l|p|h|a|a|e|t|i|c|a|l

If an element is > b we lower ub, if element is < b we raise lb

We keep sorting, get to

    a|a|a|b|h|e|t|i|c|p|l|l
    ub == lb == 3

So we recurse over the first four elements and the rest of the list, and the list is eventually sorted!