1. COT 5405: Design and Analysis of Algorithms Cliff Zou Spring 2015

2. 2 Course Information  Teacher: Cliff Zou  Office: HEC243 407-823-5015  Email: czou@cs.ucf.educzou@cs.ucf.edu  Office hour: TuTh 9:00am-10:30am  Course lecture time: TuTh 12:00pm – 1:15am (NSC-116)  Course Main Webpage:  http://www.cs.ucf.edu/~czou/COT5405-15 http://www.cs.ucf.edu/~czou/COT5405-15  Use the UCF WebCourse for homework submissions, discussion, and grading feedback  TA: Frank Plochan frank.plochan@knights.ucf.edufrank.plochan@knights.ucf.edu  TA office hour: TBD

3. Textbook 3 “Algorithm Design”, by Jon Kleinberg and Éva Tardos, 2005, Addison-Wesley.

4. Assignments  Tentative Plan:  3 written homework: 30%  2 programming assignments: 25%  Mid-term exam: 20%  Final exam: 25%  Assignments should submit through WebCourse. 4

5. Definition of Algorithm  An algorithm is a sequence of unambiguous instructions for solving a problem, i.e., for obtaining a required output for any legitimate input in a finite amount of time.  Its operations must all be sufficiently basic that they can in principle be done exactly and in a finite length of time by someone using pencil and paper. -- Knuth 5

6. Prerequisites  COP 3503 and COT 3100  Have sound programming skill  We will probably have two programming assignments  Language is in your choice  Knowledge on Basic data structure, algorithm  Assuming that you have learned data structure in undergraduate program  Knoweledge of: Stacks and queues, Sorting, Searching, Graph algorithms, String processing 6

7. This Class  Design and analysis of algorithms.  Greedy.  Divide-and-conquer.  Dynamic programming.  Network flow.  Randomized algorithms.  Intractability.  Approximation.  Emphasizes critical thinking, problem- solving, and rigorous analysis. 7

8. Why Study Algorithms?  Wide range of applications.  Caching.  Compilers.  Databases.  Scheduling.  Networking.  Data analysis and data mining.  Signal processing.  Computer graphics.  Scientific computing.  Operations research.  Artificial intelligence.  Computational biology. ...  Focus on algorithms/techniques that are useful in practice. 8

9.  Questions?? 9