• Catalog description. Design of efficient algorithms for practical data structures in engineering applications. Models of computation. NP-completeness.
• Coursework. Coursework will consist of weekly homeworks, two midterms, and a comprehensive final exam. The overall grade will be determined 20% from homework, 25% from each midterm, and 30% from the final. Group work on homeworks is permitted, but each student must list his or her collaborators in writing for each problem. If a student turns in a solution without listing the others who helped produce this solution, this act will be considered cheating (for it is plagarism). Late homework assignments will not be accepted.
  
• Exam policy. Exam performance must be 100% individual effort; no collaboration is allowed on exams. Any collaboration or copying on exams will be considered cheating. In addition to the procedures of the ICS Cheating Policy, students caught cheating on exams will be given a failing grade in the class.
• Text.
  • Required: Goodrich and Tamassia, Algorithm Design, John Wiley & Sons, ISBN 0-471-38365-1.
  • Recommended: Mehlhorn and Naher, LEDA: A Platform for Combinatorial and Geometric Computing, Cambridge Univ. Press, ISBN 0-521-56329-1.
• Add/drop policy. Drops will be accepted only up to the first midterm. Once your drop card has been signed, further coursework from you will not be graded. After the seventh week of classes, withdrawals will be allowed only by petition and under documented extenuating circumstances.

Tentative Schedule

• Week 1:
• Introduction. Algorithm Experimentation. Stacks and queues. Vectors and Lists.
• Week 2:
• Trees. Priority queues and heaps.
• Week 3:
• Dictionaries and hash tables. Binary Search Trees.
• Week 4:
Midterm I

• Splay trees. Skip Lists.
• Week 5:
• Greedy method. Divide-and-conquer. Dynamic programming. Merge-sort. Quick-sort. Sorting lower bound. Radix-sort.
• Week 6:
• Selection. The greedy method. Dynamic programming.
• Week 7:
• Graphs. Graph traversal. Depth-first search.
• Week 8:
Midterm II

• Weighted graphs. Shortest paths.
• Week 9:
• Minimum spanning trees. FFT.
• Week 10:
  • NP-Completeness. Approximation algorithms.

Copyright © 2002 Michael T. Goodrich, as to all lectures. Students are prohibited from selling (or being paid for taking) notes during this course to or by any person or commercial firm without the express written permission of the professor teaching this course.