Text: Introduction to Algorithms, 3rd Edition, by Thomas Cormen, Charles Leiserson, Ronald Rivest, and Clifford Stein, MIT Press, 2009.

This course is an introduction to algorithms. We will learn what algorithms are, why we should study them, basic techniques for implementing algorithms, and the basics of analyzing algorithms. We will cover design techniques like divide-and-conquer, dynamic programming, and greedy algorithms. In addition, we will study some of the most common and fundamental algorithms used in Computer Science such as searching, sorting, hash functions, data compression, and graph algorithms.

Your grade for this course will be based on 8 to 10 homework assignments and two exams in the following manner:

           50%    homework assignments,
           25%    exam 1,
           25%    exam 2.

           Exam 1   Tuesday, October 11,
           Exam 2   Final exam week.

You should turn in your own work for each homework assignment. Here is what that means: You may talk with your classmates about the course material and the ideas behind each homework assignment but you should solve the problem on your own and write your own solution. Turning in someone else's solution (or even a modified version of someone else's solution) is a breach of academic integrity. Similarly, giving a copy of your solution to someone else in the class is also a breach of academic integrity. If you need help with a homework assignment, come and ask me. You can ask me as many questions as you want! Please do not hesitate to ask me questions after class, in my office, in an e-mail message, over the phone, etc.

In this web site you will find more information about this course. There are links to online information about algorithms, information about course reading assignments, and, very importantly, your homework assignments and their due dates will be posted on one of the web pages.

The computer software that you need to do any programming assignments are on computers in the Mathematics Computer Labs in CLO 363 and CLO 365.

The learning objectives for this course are as follows.

1. Understand big O, omega, and theta notation and know how to use this notation to describe the complexity of algorithms.
2. Understand fundamental sorting algorithms and implement the most common quadratic and O(n log n) sorting algorithms.
3. Learn basic algorithm design techniques: greedy, divide-and-conquer, and dynamic programming. For each of them, identify an example of a simple algorithm that exemplifies the basic concept.
4. Solve problems using the fundamental graph algorithms, including depth-first and breadth-first search, single-source and all-pairs shortest paths, minimum spanning tree algorithms.

If you are a student with a documented disability who will require academic/classroom accommodations in this course, please register with the Coordinator of Services for Students with Disabilities in the Student Support Services Office located in the Student Union and Library Building (SUL), Room 341, phone numbers: 219-989-2455, 219-989-2454(voice/TTY) or 219-989-2920.

Ethics are an integral part of being a student and a professional. Academic integrity is the hallmark of this University. Therefore, Purdue University does not tolerate academic dishonesty in any form. If a student breaches integrity, the student risks sanctions in both the academic and conduct arenas. Academic dishonesty includes, but is not limited to, the unauthorized use of other's intellectual property (plagiarism), and lying to an instructor or any University employee. Such actions WILL result in a failing grade on the assignment with the strong possibility of referral to the Office of the Dean of Students for a conduct sanction (see the Purdue University Calumet Student Handbook available from the Dean of Students office and the Dean of Students web site).