These are some of the books we've found interesting or useful.
Data Mining: Concepts and Techniques
Jiawei Han and Micheline Kamber, Morgan Kaufmann
Good algorithm descriptions. Covers the major areas in reasonable
technical detail, with several alternative algorithms presented
for classification, prediction, association rule induction and cluster
Algorithms in C++
Robert Sedgewick, Addison-Wesley
If you're looking for something more readable than Knuth,
then Sedgewick fits the bill. Cited is the 3rd edition based on C++,
which I'm less familiar with than my
much older edition
which used Pascal
The advantage of Sedgewick is his readability and wide range of topics. I've
used an earlier edition of this work to find and implement many useful algorithms.
Warning: later editions aim to be more comprehensive — I think readability suffers a little as a result. Personally I prefer the older editions.
The Art of Computer Programming: Volumes 1-3
Donald E. Knuth, Addison-Wesley
If you are a computer science professional you probably already own these books.
Need to know the computational complexity of Quicksort? The worst case performance?
The conditions under which the worst case performance will occur? A method of choosing a random
record from a sequential file of unknown size? How to multiply large numbers efficiently? How
to sort with limited memory? How to sort with less comparisons than N logN?
It is rare, indeed that you can't find the answer you need in Knuth.
These are reference books, however. Don't expect to work through
them and answer all the questions at the end of each chapter. (Some of the questions
are literally PhD topics!) If you are serious about computer science,
you should have a working knowledge of what is in these
books so that you can refer to them when necessary. And, of course, you should have
them in easy reach so that you have the answers when you need them!
Data Mining for Association Rules and Sequential Patterns
Jean-Marc Adamo, Springer
Strictly a specialist book. The title says it all.
Jon Bentley, Addison-Wesley
I can still remember vividly reading the first edition of this book, as well as the column on which it was based. Bentley tackles pratical programming problems he has encountered, moving clearly from problem to solution (and explainingsome of the pitfalls) in the way only a seasoned professional can.
Key parts of problem solving is solving the right problem and choosing the right solution. You can't help but improve both skills reading this book.
The (New) Turing Omnibus: 66 Excursions in Computer Science
A. K. Dewdney, W H Freeman & Co
There are lots of algorithms out there to do lots of things... But
what are the most interesting and important algorithms in Computer Science?
I think Dewdney's book answers this question, and does it in an entertaining
and thoughtful way. This is not a book from which to implement algorithms
(there isn't always sufficient detail for that), but it is a readable book
with which to acquaint yourself with some of the most important problems
and solutions in computer science.
Note: if you didn't major in computer science, this book contains the key algorithms you should know and probably missed.
Computational Geometry and Computer Graphics in C++
Michael J. Laszlo, Prentice Hall
An area which Knuth doesn't really cover is
This introductory book explores some of the basic algorithms in computational geometry,
dealing with convex hulls, point enclosure, polygon clipping, hidden surface
removal, line intersection, closest points, range searching with grids,
The topics are covered clearly, and well explained.
(The introductory chapters of this book also contain one of the best descriptions of complexity measures and
"Big-O" notation I have come across.)
Note. One of the reviewers on Amazon.com comments that this book omits some
recent and faster algorithms for performing some key tasks. This may or may
not be important for you.
The 85 Ways to Tie a Tie: The Science and Aesthetics of Tie Knots
Thomas Fink and Yong Mao, Fourth Estate
What's a book about tying a tie doing in a list of recommended
books on algorithms?
The answer is that this book clearly demonstrates how to analyze and
solve a complex problem. Fink and Mao develop a mathematical notation
for different tie knots, identify key criteria related to aesthetics
and tie length, then use those criteria to generate
all possible tie knots, identifying the 13 with the greatest aesthetic
The book also contains an entertaining history of ties: you'll certainly
want to try some different tie knots after reading the book.
A Programmer's Geometry
Adrian Bowyer and John Woodwark, Butterworth-Heinemann
If you just want to find intersections of lines, intersections of lines with
planes, and so forth then something like Laszlo is overkill.
This older title gives you what you need, including consideration of all the degenerate
conditions which have to be taken into account, and which are often omitted from
more cursory treatments of the topic.
This book is out of print and can be a little hard to find. The library of a company I worked for used to have a copy, and it proved an invaluable reference.
Data Model Patterns: Conventions of Thought
David C. Hay, Dorset House Publishing
This is a useful introductory text
on systems analysis. Most books in this category are too academic: systems analysis
is a pratical art. Rather than give lots of theoretical example, this book gives
typical solutions for common corporate functions, along with explanations of why
the design is the way it is and not what you might have thought it should be.
Worth a read if you're new to the art, as it will definitely save you from
making some easy mistakes.
24 Deadly Sins of Software Security: Programming Flaw and How to Fix Them
Michael Howard, David LeBlanc, John Vega, McGraw Hill
Most books about hacking and software vulnerabilities are terrible. This one is actually quite good.
The reason most books are terrible is that they concentrate on specific vulnerabilities and don't draw general lessons. The information they give therefore relates to very specific vulnerabilities which are generally long-fixed by the time the book appears in print. They offer little of interest either for the hacker, or for the software designer or programmer who must design a secure system. You can probably find a dozen such books discarded in your local thrift store.
This book is actually one worth having.
The authors provide general observations of classes of errors, along with examples of when these errors have been made in the past, and how to identify such errors in a design or source code. It's not a perfect book: too much of the early chapters are spent demonstrating particular coding errors in a variety of computer languages , and perhaps some of the later chapters are too cursory as a result — but it's one of the few books on the topic that I expect to be worth keeping and re-reading in more than a year's time.