Techniques and principles of algorithms design including divide-and-conquer and greedy algorithms. Complexity (worst and average case) analysis and their associated asymptotic notations (Theta, Big O, Omega). Iterative sorting algorithms: Bubble sort, insertion sort. Recursive sorting: merge sort, quick sort, heap sort. Sorting in linear time: counting/radix sort. Decision tree analysis: N*logN bound on comparison based sorting.  Algorithms for graph problems: Shortest path (Dijkstra), minimum spanning trees (MST algorithms: Kruskal, Prim). Hashing. Discussion on NP-class problems (e.g. Travelling Salesman Problem).

• CSC 203 + Lab : Data Structure

• Students will learn methods for designing efficient algorithms, evaluating their performance, and ways of establishing precise limits on the possible effectiveness of classes of algorithms
• They will learn standard algorithms for fundamental problems.

1. Algorithms (4th Edition) by R. Sedgewick, K Wein
2. Introduction to Algorithms (2nd Edition) by T. Cormen, C. Lieserson, R. Rivest, C. Stein
3. Art of Computer Programming Vol. 1 (Fundamental Algorithms) by D. Knuth

Biweekly Quiz, One Midterm Exam, One Final Exam, Project