Time and Place: Tuesdays and Fridays, 2:00pm-3:50pm, Location TBD

Instructor: Elliot Anshelevich
311 Lally Hall, 518-276-6491

Announcements and Handouts:
01/01/10 - This is where various announcements will appear during the semester.

Course Overview

This course presents fundamental ideas and techniques of modern algorithm design and analysis. After completing this course, students should be able to analyze and design efficient algorithms for a variety of computational problems. For more details, see the Syllabus.

Pre-requisites

The official prerequisites for the course are CSCI 2300 and MATH 2800. We will assume that everyone has seen the material in in these courses, and will use it as necessary.

• Specifically, from CSCI 2300 this includes elementary data structures, binary search, sorting, big-O notation, and basic terminology involving graphs (including the concepts of depth-first search, breadth-first search, and connectivity). These topics are covered in chapters 2 and 3 of the textbook.
• The prerequisites for this course also include a background in discrete mathematics, including order of function growth, sets, recurrence relations, and proof techniques such as induction and contradiction. The lectures and homework involve the analysis of algorithms at a fairly mathematical level. We expect everyone to be comfortable reading and writing proofs, at the level of MATH 2800.

Textbook

The course textbook is Algorithm Design by Jon Kleinberg and Éva Tardos. It is available at the campus store.

Although the lectures will mostly be drawn from the textbook, we will still cover things that do not appear in the text, and the textbook includes material that we will not cover in class. You are responsible for the content of the lectures as well as any assigned readings. You may also find the following books useful for reference and for different perspectives:

• Cormen/Leiserson/Rivest/Stein: Introduction to Algorithms.
• Aho/Hopcroft/Ullman: The Design and Analysis of Computer Algorithms.
• Dasgupta/Papadimitriou/Vazirani: Algorithms.
• Garey/Johnson: Computers and Intractability.
• Kozen: The Design and Analysis of Algorithms.

Homework, Exams, and Grading

Students are encouraged to attend all classes. Your active in-class participation will be a substantial part of your learning process, and will be taken into consideration when final grades are determined.

Homework. Homework will be assigned every 1-2 weeks. There will not be any programming assignments. Homework should be handed in at the beginning of lecture on the day it is due. For more information about homework, see the 4020 Homework Guide.
You are required to prove your statements, unless otherwise specified. If a homework or exam question asks you to design an algorithm for a certain task, then the answer must consist of a description of the algorithm (an English description is fine), as well as an analysis of its running time and a proof of its correctness.

Exams. There will be a midterm exam in class on March 19th, and a comprehensive final exam during finals week. There will also be an in-class quiz during the second week of class testing knowledge that is pre-requisite for this class. All exams are open-textbook and open-notes. Make-up tests or homework assignments will not be given except in case of an emergency. Students who know they are going to miss a test must notify me in advance. Special circumstances can be accommodated if I am notified about them in advance.

Grading. The midterm will count for 20% of your final grade, the final for 25%, and the homework for 50%. The quiz during the second week of class will count for the remaining 5%.
Regrades: Any request to re-evaluate a grade must be made within one week of the return date of the homework or exam in question. You must explain why you think your grade should be changed in writing, and submit your request to me or a TA, together with the original problem solution. The second grade will remain.
Final Grades: Final scores will correspond to the following letter grades: A: 85-100; B: 75-85; C: 60-75; D: 50-60
For PhD students: This course will give you an automatic pass for a qualifying exam in Computer Algorithms if your final grade is an A (an A- will not be sufficient). Note that a total score of at least 90 percent will result in an automatic A grade for the course.

Policy on Academic Integrity: You are allowed (and encouraged) to discuss homework problems with other members of the class, and to formulate ideas together. However, everyone must write up their assignments separately, and include the names of everyone you discussed the assignment with. You may not copy (or near-copy) a solution from another. Failure to write the solution to a homework completely on your own will be considered a breach of academic integrity, and may result in the final grade being reduced by a letter and a 0-grade for the homework for both parties. No collaboration is allowed during exams.