CPS 130: Introduction to the Design and Analysis of Algorithms |
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Description:
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 divide-and-conquer, 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.
Prerequisites:
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.
Meetings:
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Times: Tues & Thurs 2:50 PM – 4:05 PM Room: Languages 211 |
Instructor:
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Professor John Reif |
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Office: |
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D223 LSRC Building |
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Phone: |
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(919) 660-6568 |
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Email: |
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Web page: |
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Office hours: |
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Tues, Thurs: 4:05 pm - 5:00 pm |
Recitation by TA:
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CPS130-01R Recitation by TA |
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Times: Friday
1:15PM – 2:30PM Room: Languages
211 |
TA:
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Office: |
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D330 LSRC Building |
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Phone: |
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(919) 660-6589 |
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Email: |
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Web page: |
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Office hours: |
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Tues, Thurs: 4:05 pm - 5:00 pm |
Course material:
- Text Book: [CLRS] Cormen, Leiserson, Rivest, and Stein. Introduction
to Algorithms, McGraw
Hill, third edition, 2009. Be sure to get the third edition
· Solutions to Selected exercises and
problems in CLRS
- Lectures: Various lecture notes and research
papers (downloadable).
Optional auxiliary reading (other good reference
books):
- G. Brassard and P. Bratley. Algorithmic
- Theory and Practice. Prentice Hall, 1988.
- D. Kozen. The Design and Analysis of Algorithms.
Springer Verlag, 1991.
- A. Aho, J. Hopcroft, and J. Ullman. Design and
Analysis of Algorithms. Addison Wesley 1974.
- R. Tarjan. Data Structures and Network Algorithms.
SIAM Publications, 1983.
- C. H. Papadimitriou. Computational
Complexity. Addison Wesley, 1994.
Course synopsis:
- Mathematical Analysis of Algorithms:
growth of functions, summations, recurrences, average-case and randomized
analysis
- Sorting and selection:
divide-and-conquer and randomized techniques
- Search trees: search trees
- Amortized analysis
- Priority queues
- Greedy algorithms
- Dynamic programming
- Graph algorithms
- Matrix and algebraic algorithms
- Approximation algorithms
Summary of topics covered and
lecture notes:
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.
Homework assignments:
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.
Grading:
- Class Interaction (10%)
- Homework assignments (20%)
- Closed-book quiz 1 (10%)
- Closed-book midterm exam 2 (15%)
- Closed-book lateterm exam 3 (15%)
- Closed-book final exam (30%)
- Optional Class Project (only if
approved by instructor)
There will be no make-up exams for missed exams. Missing one
of the three midterm exams due to an illness requires filing the web-based
Short-Term Illness Notification Form at http://www.aas.duke.edu/trinity/t-reqs/illness,
and will result in the remaining midterm exams grades being re-weighted (to 20%
each). By University Policy, missing the Final exam results in a grade X.
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