UMBC CMSC441, Design & Analysis of Algorithms, Fall 1999, Section 0101
Course Description
Textbook
Introduction to Algorithms, Cormen, Leiserson and Rivest, McGraw-Hill.
Prerequisites
You should have mastered the material covered in the
following courses: CMSC 203 (Discrete Structures), CMSC 341 (Data
Structures) and MATH 152 (Calculus and Analytic Geometry II). The material
in Chapters 5, 11 and 13 of the textbook (covering sets, elementary data
structures and binary search trees) should be familiar. Some knowledge of
probability and counting (Sections 6.1-6.4 of the textbook) is also
expected. In addition, proficiency in the implementation of the elementary
data structures (e.g. stacks, queues, linked lists, binary trees and
graphs) in C/C++ or Java is assumed.
Objectives
This course stresses the quantitative methods used in
the design and analysis of algorithms. The main emphasis of this course is
to help you develop the skills needed to analyze the running times of
algorithms and to prove the correctness of algorithms. A secondary goal of
this course is to familiarize you with a broad range of fundamental
algorithms. The material covered in this course will include algorithms
for sorting, order statistics, hashing, balanced binary trees, dynamic
programming and graphs. If time permits, a selection of advanced topics
(such as cryptographic algorithms, NP-completeness, Strassen's algorithm
or parallel algorithms) may also be included.
Your final grade will be based upon class participation (2%), a programming
project (10%), homework assignments (40% total), Exams 1 & 2 (14% each)
and the final exam (20%). It is very important that you do the weekly
homework assignments. The homework assignments count for a major portion of
your grade --- more than each exam. Your grade is given for work done
during the semester; incomplete grades will only be given for
medical illness or other such dire circumstances.
Your final letter grade is based on the standard formula:
0 <= F < 60, 60 <= D < 70, 70 <= C < 80,
80 <= B < 90, 90 <= A <= 100
Depending upon the distribution of grades in the class, there may be a
curve in your favor, but under no circumstances will grades be curved
downward. As a guideline, we expect that a student receiving an
"A" should be able to solve the homework problems with facility;
design and analyze new algorithms in written exams; and demonstrate an
understanding of the impact of theoretical analysis in practical
programming settings.
Lecture and Homework Policy
You are expected to attend all
lectures. You are responsible for all material covered in the lecture as
well as those in the assigned reading. However, this subject cannot be
learned simply by listening to the lectures and reading the book. In order
to master the material, you need to spend time outside the classroom, to
think, to work out the homework and understand the solutions.
There will be a total of 11 homework assignments. The homework average
will be computed from your 10 best homework grades. Homework is due at the
beginning of lecture --- this is so you do not work on your homework
during lecture. Late homework will not be accepted --- this is to
allow for timely grading and discussion of the homework solutions.
Since you will be given partial credit for serious attempts, you should
simply turn in whatever you have accomplished for the homework set when it
is due. A good approach to solving the homework problems is to work on one
problem each day and to come to class or office hours with prepared
questions about the problems you have not been able to solve.
Working Together
You are encouraged to work with other students
and to consult other reference books. However, you must acknowledge your
collaborators and reference materials by listing them on the last page of
your homework. Also, you must write up your homework independently.
This means you should only have the textbook and your own notes in front
of you when you write up your homework --- not your friend's notes,
your friend's homework or other reference material.
You should not have a copy of someone else's homework or project under
any circumstance. For example, you should not let someone turn in your
homework. Cases of academic dishonesty will be dealt with severely.
Exams:
The exams will be closed-book and closed-notes. The dates
for Exams 1 and 2 are Thursday, October 7 and Tuesday, November 9. If you
miss an exam for good reason (e.g., medical illness), the average score of
the remaining exams will be used in place of that exam.
The final exam will be comprehensive and cover the material from the
entire course. The final exam may be a combined final exam for both
sections of this course, so the time and location of the final exam might
differ from those listed in the class schedule. Details on the final exam
will be announced soon.
Last Modified:
22 Jul 2024 11:29:15 EDT
by
Richard Chang
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