Fall 2011

This course is for undergraduate students to learn basic concepts and techniques in

algorithms and complexity.

Lectures. Tuesday and Thursday, 3:30-4:45 pm.

Instructor: Yufeng Wu (ywu@engr.uconn.edu), ITE 235. Office hour: Tuesday and Thursday,

9:00-12:00.

Prerequisites. CSE 2100 (Data structure and intro. to algorithms) and CSE 2500

(Introduction to discrete systems). Some topics need some basic knowledge of probabilities.

Textbook: The required textbook is: Introduction to Algorithms (3nd edition) by T. Cormen, C. Leiserson,

R. Rivest, and C. Stein, 2009. Most of the lectures are based on this book, although we will sometimes

cover some topics not in the book (where notes and handout will be provided) and of course

we can not cover every chapter of the book.

Outline. This course is lecture-based. The planned subjects are the following (subject to change).

1) Fundamental concepts of algorithms. Asymptotic order of growth. Basic running time analysis.

Divide and conquer. Basic probabilistic analysis. Different kinds of sorting.

2) Basic algorithm techniques. Dynamic programming. Greedy algorithms. Algorithms for graphs:

basic algorithms, minimum spanning tree and shortest path.

3) Advanced algorithms and complexity. NP-completeness. Randomized algorithms.

Introduction to approximation algorithms. Algorithms on strings.

Homeworks. We will have homework every one to two weeks. Work hard on them, although

homeworks do not carry big weights on grading. This is the best way to prepare for exams.

Much of what you learn from this course comes from the homeworks. Your solutions should be

concise, correct and legible. Some of the problems may be challenging, depending on your

background. If you can not solve a problem, briefly explain where the difficulty is.

Note: you need to acknowledge any source of ideas other than the textbook. You must always

write the solutions on your own.

Exams. There are two midterm exams for this course and a final exam. Exams will be closed book.

We will have additional review sessions to help students prepare for the exams. Be there if you can.

Grading. Homeworks (25%), mid-term 1 (20%), mid-term 2 (25%) and final (30%).