CPS 130: Introduction to the Design and Analysis of Algorithms 
This course is an introductory undergraduate
course on the design and analysis of algorithms. The course builds on the study
of the analysis and implementation of data structures and algorithms from
CPS100. The goal is to introduce a number of important algorithm design
techniques as well as basic algorithms that are interesting both from a
theoretical and also practical point of view. We will cover basic algorithm
design techniques such as divideandconquer, dynamic programming, and greedy
techniques for optimization. We will cover techniques for proof of the
correctness of algorithms and also asymptotic analysis of algorithm time bounds
by the solution of recurrence equations. We will apply these design and
analysis techniques to derived algorithms for a variety of tasks such as
sorting, searching, and graph problems. Some specific algorithm topics include:
deterministic and randomized sorting and searching algorithms, depth and
breadth first search graph algorithms for finding paths and matchings, and
algebraic algorithms for fast multiplication and linear system solving.
CPS 100 or equivalent and four semesters of college
mathematics. This course requires undergraduate background in data structures
(as covered in CPS100) as well as a certain amount of mathematical
sophistication (e.g., as required to solve recurrence equations). A quiz on
recurrence equations early in the course will provide you with some feedback on
whether your mathematics training will suffice. If you feel that you may not
have sufficient background, please talk with the instructor John Reif.

Times: Tuesdays and Thursdays 4:25PM  5:40PM Room: D106 LSRC Building 
Professor John Reif 

Office: 

D223 LSRC Building 
Phone: 

(919) 6606568 
Email: 


Web page: 


Office hours: 

Tues, Thurs: 2:00 pm  3:00 pm 
Thursday (Recitation #CPS13001R): 

Times: Th 3:05PM  3:55PM Room: North 225 
Friday (Recitation #CPS13002R): 

Times: F 10:20AM  11:10AM Room: North 225 
Optional auxiliary reading (other good reference
books):
Consult the schedule of lecture
topics for a list of topics and a copy of lecture notes for the lectures to
date. Other handouts can be found in the handouts
directory, and homeworks and old midterm and final exams can be found in
the homework directory. See resources
page for additional information.
Homeworks are due roughly every
week and must be turned in before class on Wednesday of the week they're due. No
credit is given for late solutions. For exceptional circumstances, see John Reif in advance, rather than
after the due time. Homework
assignments will be archived in the homework directory.
The postscript version, pdf version, and source LaTeX code will be available
for each homework problem.
Details about proper style [ps] for writing up homework solutions and
some guidelines for grading are available. More detailed notes on how to write up
technical material [ps.gz] in
the Computer Science field (much of which is beyond the scope of this course)
are available.
It is recommended but not
required that LaTeX be used for typesetting homework problems. You can make use
of the LaTeX
source file, the LaTeX
macros, a LaTeX
template file, a LaTeX
guide, and hypertext
LaTeX help.
Honor code: For homework problems, discussion among students
is permitted, but students MUST write up solutions independently on their own. No materials or sources
from prior years' classes or from the Internet can be consulted. Breaking
the rules can result in expulsion. Each student is required to make a copy of this page, sign it indicating
that the contents are understood, and turn it in to John Reif.
There will be no makeup exams for missed exams. Missing one of the three midterm exams
due to an illness requires filing the webbased ShortTerm Illness Notification
Form at http://www.aas.duke.edu/trinity/treqs/illness,
and will result in the remaining midterm exams grades being reweighted (to 20%
each). By University Policy, missing the Final exam results in a grade X.
Last Modified: