1. UMass Lowell Computer Science 91.404 Analysis of Algorithms Prof. Karen Daniels Spring, 2001 Lecture 1 Introduction/Overview Wed. 1/31/01

2. Web Page http://www.cs.uml.edu/~kdaniels/courses/algorithms2001spring.html Web Page

3. Nature of the Course ä Core course: required for all CS majors ä Advanced undergraduate level ä Graduate students take separate course (91.503) ä No programming required ä “Pencil-and-paper” exercises ä Lectures supplemented by: ä Programs ä Real-world examples

4. What’s It All About? ä Algorithm: ä steps for the computer to follow to solve a problem ä Some of our goals: ä recognize structure of some common problems ä understand important characteristics of algorithms to solve common problems ä select appropriate algorithm to solve a problem ä tailor existing algorithms ä create new algorithms

5. Some Algorithm Application Areas Computer Graphics Geographic Information Systems Robotics Bioinformatics Astrophysics Medical Imaging Telecommunications Design Apply Analyze

6. Original Points Sample Problem: Nearest Neighbor Voronoi Diagram Bioinformatics Telecommunications New Point

7. Tools of the Trade ä Algorithm Design Patterns such as: ä binary search ä divide-and-conquer ä Data Structures such as: ä trees, linked lists, hash tables, graphs ä Theoretical Computer Science principles such as: ä NP-completeness, hardness Growth of Functions Summations Recurrences Sets Probability MATH Proofs

8. Tools of the Trade: (continued) Algorithm Animation http://www.cs.brockport.edu/cs/java/apps/sorters/insertsortaniminp.html

9. Prerequisites ä Computing I (91.101) ä Computing II (91.102) ä Discrete Math I & II (92.321, 92.322) ä Statistics for Scientists and Engineers (92.386) ä Calculus I-III (92.131-231) Growth of Functions Summations Recurrences Sets Probability MATH Proofs

10. Course Structure: 4 Parts ä Discrete Math Review ä Growth of Functions, Summations, Recurrences, Sets, Counting and Probability ä Sorting ä Heapsort, Priority Queues, Quicksort, Sorting in Linear Time, Medians and Order Statistics ä Data Structures ä Stacks and Queues, Linked Lists, Introduction to Trees, Hash Tables, Binary Search Trees, Balancing Trees: Red-Black Trees ä Advanced Techniques ä Dynamic Programming, Greedy Algorithms, Graphs

11. Textbook - - Required: ä Introduction to Algorithms ä by T.H. Corman, C.E. Leiserson, R.L. Rivest ä McGraw-Hill + MIT Press ä 1993 ä ISBN 0-07-013143-0 ä see course web site (MiscDocuments) for errata Available in UML bookstore

12. Syllabus (current plan)

13. Syllabus (continued)

14. Important Dates ä Exam:Friday, 2/23 ä Midterm Exam:Friday, 3/16 ä Final Exam:TBA

15. Grading ä ä Homework40% ä ä Exam (Chapters 1-6) 15% (closed book) ä ä Midterm (Chapters 1-10) 20% (open book, notes ) ä ä Final Exam25% (open book, notes )

16. Homework 1 Fri, 2/2 Fri, 2/9 Chapters 1, 2 HW# Assigned Due Content