Second Edition now available!
This newly expanded and updated second edition continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.
The readerfriendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography.
The second edition contains enough material to serve as the textbook
for a standard Introduction to Algorithms course.
I assume the reader has completed the equivalent of a second programming
course, typically titled Data Structures or Computer Science II.
The book, and associated supporting material, stresses design over analysis.
A full set of
lecture slides
integrated with
audio and video lectures are freely available on line.
Let me help teach your course!
I received the 2001
IEEE Computer Science and Engineering Teaching Award and have been been teaching undergraduate algorithm
classes for almost twenty years.
I have made several pedagogical
improvements throughout the book.
Textbookoriented features include:

More Leisurely Discussion 
The tutorial material in the first part of the book has been
doubled over the previous edition.
The pages have been devoted to more thorough and careful exposition
of fundamental material, instead of adding more specialized topics.

False Starts 
Algorithms textbooks generally present important algorithms as a
fait accompli, obscuring the ideas involved in designing them and
the subtle reasons why other approaches fail.
The war stories illustrate such development on certain applied problems,
but I have expanded such coverage into classical algorithm design
material as well.

Stop and Think 
Here I illustrate my thought process as I solve a topicspecific
homework problemfalse starts and all.
I have interspersed such problem blocks throughout the text to increase
the problemsolving activity of my readers.
Answers appear immediately following
each problem.

More and Improved Homework Problems 
This edition of The Algorithm Design Manual has
twice as many homework exercises as the previous one.
Exercises that proved confusing or ambiguous have been
improved or replaced.
Degree of difficulty ratings (from 1 to 10) have been assigned to
all problems.

SelfMotivating Exam Design 
In my algorithms courses, I promise the students that
all midterm and final exam questions
will be taken directly from homework problems in this book.
This provides a ``studentmotivated exam,'' so students know exactly
how to study to do well on the exam.
I have carefully picked the quantity, variety, and difficulty of
homework exercises to make this work; ensuring
there are neither too few or too many
candidate problems.

TakeHome Lessons 
Highlighted ``takehome'' lesson boxes scattered throughout the
text emphasize the bigpicture
concepts to be gained from the chapter.

Links to Programming Challenge Problems 
Each chapter's exercises will contain links to 35 relevant
``Programming Challenge'' problems from
http://www.programmingchallenges.com.
These can be used to add a programming component to paperandpencil
algorithms courses.

More Code, Less Pseudocode 
More algorithms in this book appear as code (written in C)
instead of pseudocode.
I believe the concreteness and reliability of actual tested implementations
provides a big win over less formal presentations for simple algorithms.
Full implementations are available for study at \courseweb.
First Edition
I was gratified by the warm reception the first edition of
The Algorithm Design Manual received since its publication.
It ultimately went through ten printings and generated numerous
errata, which remain available here.
The first edition came with a CDROM, with mirrors of
the algorithm repository
and my
audio/video
lecture notes.
Updated and improved versions of these resources are available on line,
rendering the CDROM unnecessary (although I fondly recall the fellow
who asked me for an extra copy so their child could have one when they grew up).
This CDROM was also the source of the pirated online version from
Indonesia.
The
Amazon Kindle edition is better.
Reviews of The Algorithm Design Manual include:

From
Steve Yegge  Get that Job at Google":
`` My absolute favorite for this kind of interview preparation is Steven Skiena's The Algorithm Design Manual. More than any other book it helped me understand just how astonishingly commonplace (and important) graph problems are – they should be part of every working programmer's toolkit. The book also covers basic data structures and sorting algorithms, which is a nice bonus. But the gold mine is the second half of the book, which is a sort of encyclopedia of 1pagers on zillions of useful problems and various ways to solve them, without too much detail. Almost every 1pager has a simple picture, making it easy to remember. This is a great way to learn how to identify hundreds of problem types.''

From Programming Stuff:
``The book teaches you how to extract the relevant information from a problem, how to transform a given problem into a wellresearched problem, how to select the best data structure for the job and how to really improve algorithms. ..
That's what makes the book so different and yet so valuable.''
Written by a wellknown algorithms researcher who received the IEEE Computer Science and Engineering Teaching Award, this new edition of The Algorithm Design Manual is an essential learning tool for students needing a solid grounding in algorithms, as well as a special text/reference for professionals who need an authoritative and insightful guide.
Quotes
"...the book is an algorithmimplementation treasure trove, and putting all of these implementations in one place was no small feat. The list of implementations [and] extensive bibliography make the book an invaluable resource for everyone interested in the subject." ACM Computing Reviews
"It has all the right ingredients: rich contents, friendly, personal language, subtle humor, the right references, and a plethora of pointers to resources."
 P. Takis Metaxas, Wellesley College
"This is the most approachable book on algorithms I have."
 Megan Squire, Elon University, USA