Instructor. Richard Cole, WWW412, tel: 998-3119, email@example.com.
Lectures: Mon-Wed 1:20-2:35, room 101, Warren Weaver Hall.
Recitation: Tues 1:20-2:35, room 101, Warren Weaver Hall.
First meeting: Wednesday, September 9.
Office hours. Mon. 2:45-3:45pm, Wed. 2:45-3:45, and by appointment.
Mailing list, home page. There is a class mailing list at v22_0310_001_fl98@cs; please join this list; it is intended for discussion of course related materials and announcements if there are any (to subscribe, send mail to Majordomo@cs.NYU.EDU with a body of SUBSCRIBE v22_0310_001_fl98). The course home page can be accessed from the department home page (http://cs.nyu.edu/) by following the links to course home pages and then to this course, or directly at
Syllabus. This course will study the fundamentals of data structure and algorithm design, including methods for determining the (asymptotic) running time of algorithms. A detailed syllabus can be found here. Topics to covered include: Order of magnitude growth (e.g. O(n), O(n log n), O(n^2)), solving recurrence equations, sorting, balanced trees, graph algorithms, divide and conquer, dynamic programming.
Assignments. There will be more or less weekly homeworks comprising problems drawn from the textbook and elsewhere. Late homeworks will not be accepted (except in the event of illness or other unavoidable circumstances). If for some reason you will be unable to hand in a homework on time, please discuss it with me beforehand.
Assessment. There will be one or more midterms, counting 0-25% toward the final grade. The final exam will comprise 50-75% of the course grade, depending on how the midterms are counted. If the grade for the final is better than the grade for the midterms, the final grade will be used instead of the midterm grade. Homework will count for 25%.
Siegel and Cole, An Inside guide to Algorithms. Photocopied Lecture Notes.
These are available, as of 9/5/98, for purchase at Unique Copy, 252 Greeene St; hours: 8am to 11pm, Mon-Fri; 10am-8pm, Sat-Sun.
Other texts which can be used as alternate texts include:
Aho, Hopcroft and Ullman. Data Structures and Algorithms.
Cormen, Leiserson, Rivest. Introduction to Algorithms.
Brassard and Bratley. Algorithmics, Theory and Practice.
firstname.lastname@example.org (Richard Cole)