Problems on Algorithms | by Ian Parberry & William Gasarch
268 pages | Prentice Hall; 2nd edition (2002) | English | | 2.35 MB

$http://rapidshare.com/files/18869941/Prentice_Hall_-_Problems_On_Algorithms.pdf

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Too often the problem sets in standard algorithm texts are composed of
small, idiosyncratic units of busy-work and irrelevant questions --
forcing instructors into the time-consuming task of finding or
composing additional problems. Designed to fill that gap, this
supplement provides an extensive and varied collection of useful,
practical problems on the design, analysis, and verification of
algorithms.


Amazon Review:
“
A little gem of fundamental computer science, July 5, 2003
Reviewer: James Arvo (Pasadena, CA USA) -

This is a terrific little book, which I recommend highly to students
of computer science, but above all to those who teach computer
science. While I could imagine teaching a short course based on this
book alone, it would be an excellent supplement to a more
thorough-going text. Better still, just keep this little book around
for those times when you are searching for a good homework or exam
problem. It's got hundreds of them.

On the down side, Parberry's discussions are so terse that students
may get somewhat frustrated if it is their only source. Yet, there is
much to be said for being concise! The author wastes nary a syllable
before launching into the problems, which is how he managed to pack so
much into a mere 167 pages. Don't be deceived by the thickness of this
book; it may look like a mere pamphlet, but it contains 651 exercises,
many of which have lengthy hints and good number of which are actually
worked out in detail.

The book introduces a wide range of topics from very basic
(mathematical induction) to somewhat sophisticated (NP-completeness).
About half of the book focuses on mathematical prerequisites such as
induction, inequalities, binomial coefficients, combinatorics, graphs,
Big-Oh & Big Omega, and recurrence relations. The rest of the book
covers topics such as graph algorithms, searching, greedy algorithms,
dynamic programming, divide-and-conquer, backtracking, program
correctness, and even a chapter on NP-completeness. The latter
includes a terse description of both Cook reducibility and Karp
(many-to-one) reducibility. This last chapter would be a bit too dense
for someone unfamiliar with these concepts, but it's a nice review
with copious exercises.

There are a few things I particularly like about the book. First is
the chapter on program correctness, which includes dozens of examples
and exercises on loop invariants. This is a great resource in itself.
Secondly, I really like the occasional "What is Wrong?" sections,
where the author presents what seems to be a valid proof or argument,
and the student is asked to find the subtle flaw. This is an excellent
pedagogical technique.

If you're an undergraduate in computer science, the simpler exercises
will be extremely useful to you. If you are a graduate student in
computer science, you will gain from seeing all these fundamental
topics covered so quickly, and with very clear examples. Read it
before your qualifying exam! If you are a professor of computer
science (like me), you may want to keep this book under wraps; it's
too good a source for exam problems.

I'll close with a paraphrasing of one of the exercises in the book.
This is significantly wordier than most of the problems in this book,
but it's clever and is exactly the type of thing that would make a
great homework exercise in an introductory algorithms class. "You are
facing a high wall that stretches infinitely in both directions. There
is a door in the wall, but you don't know how far away or in which
direction." The problem then asks you to describe how you would find
the door in O(n) steps, where "n" is the number of steps initially
separating you from the door. What a cute problem!

I wish there were more volumes like this.



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