On successful completion of this course, students are expected to be able to:

1.  Describe fundamental concepts and techniques for determining the asymptotic behavior of real-valued functions defined in natural numbers.
   
   
2. Explain recurrence equations and solve common recurrences using a variety of techniques.
   
   
3. Analyze an algorithm described in plain language or some form of pseudocode in terms of its time (or space) efficiency as a function of the size of a problem instance.
   
   
4. Explain how various data structures, including trees, heaps and disjoint set structures, influence the time efficiency of algorithms.
   
   
5. Apply general algorithmic design and analysis techniques to solving problems, including greedy, divide-and-conquer and dynamic programming.
   
   
6.  Identify randomization in algorithms and analyze basic randomized algorithms such as randomized quicksort and selection.