
Lectures  Teaching Assistant  Resources
Canvas Website
for COMPSCI 531D
Introduction to Algorithms
Course Description:
This course is an introductory graduate
course on the design and analysis of algorithms. The course builds on an
undergraduatelevel study of the analysis and implementation of data structures
and algorithms (COMPSCI 201). 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.
Lectures will focus on introducing major
algorithmic principles of design and analysis, along with mathematical analysis
of algorithmic problems. The weekly lab section will build on that material to
explore questions of implementations and applications to real world problems.
Prerequisites:
A student taking the course should
already have taken an undergraduatelevel course on data structures and
algorithms (e.g., COMPSCI 201 or equivalent) and also
four semesters of college mathematics. This course requires 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 an instructor.
Meetings (Lectures and
Recitations)
Room: LSRC
A247
Times: Tues, Wends
& Thurs 3:05 PM – 4:20 PM

Room: LSRC A247 
Instructor: Professor John Reif
Office: 

D223 LSRC Building 
Phone: 

9196606568 
Email: 


Web page: 


Office hours: 

Weds, Fri: 9:00AM – 10:00 AM – via Zoom 
TA RECITATIONS: Room: LSRC A247
TA: Vincent Li Office hours: · Tues 5pm6pm and Wed Noon1pm
(please email to reserve) · Phone: 3053387289 · Email: vincent.l.li@duke.edu 










Course material:
· Solutions to Selected exercises and problems in CLRS
Optional auxiliary reading (other good
reference books):
Course Topics:
Summary of topics covered
and lecture notes:
Consult the schedule of Lectures for a list
of topics and a copy of lecture notes for the lectures to date. See resources page for
additional information.
Homework assignments:
All assignments will be released to Students on the
course Sakai webpage, and all solutions should similarly be submitted on the
course Sakai webpage. No credit is given for late solutions. You should turn in
what you have on time for partial credit rather than receive a 0. For
exceptional circumstances, see the instructor in advance, rather than after the
due time. Our policy is that one (and only one) homework during the entire term
is allowed not to be handed in, at no loss of credit. Furthermore, if you hand
in all the homework, then we will drop the lowest graded homework.
Students will be asked to design algorithms for classic
problems and provide mathematical analysis of correctness and asymptotic
efficiency. Students will turn in a written set of solutions. It is recommended
but not required that LaTeX be used for typesetting homework problems. If handwritten solutions are illegible, they will not be graded. Details
about proper style for writing
up homework solutions and some guidelines for grading are available.
Homeworks are due roughly
every second 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.
Honor code: For
homework problems, discussion among students is permitted, but students must
write up solutions independently on their own. 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. For details about what is acceptable, see this honesty matrix.
During every exam: all calculators,
computers, cell phones, wireless or bluetoothconnected
devices, and all other electronic devices must be identified and handed over to
the person proctoring the exam. Breaking the rules can result in
expulsion. Each student is required to make a copy of this paragraph,
sign it indicating that the contents are understood, and turn it in to John
Reif.
Grading:
There will be no makeup exams
for missed exams. Missing one of the three midterm exams will result in the
remaining midterms and final exam grades being reweighted appropriately. By
University Policy, missing the Final exam results in a grade X. The grades will
be curved when calculating the final letter grade.
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