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Mastering Algorithms with Perl
Books: Text Books: Algorithms: Item 8
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Mastering Algorithms with Perlby John Macdonald, Jon Orwant, and Jarkko Hietaniemi
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10 of 10 people found the following review helpful: Nice introduction, May 9, 2001 Reviewer:Lee Carlson (Saint Louis, Missouri USA) - This book ia fairly good introduction to the use of PERL in developing and implementing various algorithms, including scientific and cryptographic ones. Fortunately, source is included, setting the book apart from the usual books on computer algorithms. The first few chapters outline PERL data structures, with the built-in data structures discussed, along with a discussion of how to create new ones. The dynamic nature of arrays in PERL is emphasized, and this is a feature that sets PERL way above other languages, such as C and C++. Linked lists are given a detailed treatment along with garbage collection in PERL. The authors are careful to point out that reference counting in PERL will fail when one is dealing with a circle of reference values. A discussion of sorting follows, with radix and hybrid sorts being the most useful of the algorithms discussed. The authors give a useful comparison study of the running time of the sorting algorithms. This is followed by a discussion of searching algorithms, which unfortunately omits any details of dynamic programming, which is useful in applying PERL to areas such as computational biology. The authors give a very interesting treatment of how to do set operations using PERL in the next chapter. They did not treat the case of fuzzy sets in detail though, unfortunately. Matrix algorithms are discussed next, with the PERL modules MatrixRead and PDL integrated into the discussion. I have only used PDL and its graphic library PGPLOT and have had varying degress of success with it. PERL still has a long way to go before it is accepted as a language suitable for numerical computations. Graph algorithms are the subject of the next chapter. The most useful section is the one on minimum spanning trees, so useful in network routing algorithms. This is followed by a thorough discussion of string algorithms in Chapter 9. These algorithms are extremely important in current applications, such as string matching and alignment in computational biology. That the authors give the source code for the algorithms is extremely helpful to those who need to apply these algorithms. The authors return to geometric algorithms in the next chapter, with only elementary ones being discussed, with brief overviews of PERL graphics modules available. Number systems and numerical precision are taken up in the next chapter, with 32 bit precision implemented in the discussion. The authors do however discuss how large number arithmetic can be implemented in PERL via the BigFloat and BigInt modules. This is followed by modular arithmetic and number theory , with PERL code given for the Miller-Rabin primality test. This chapter is very short, but it sets up the next chapter on cryptography, which begins with a discussion of passwords, with a PERL program given that checks valid passwords. Then, interestingly, a PERL 1-liner is given for cracking a password list. The discussion on passwords should be of interest to individuals first entering the field of computer security. This is followed by a fairly complete elaboration on authentication and checksums. Encryption of data is discussed in the next section, along with a brief mention of the AES, which at the time of publication of this book, was not settled. The RSA algorithm is discussed also, with a 3-line PERL code given for it, along with a more instructive version later. Only one section on steganography is included, and since this is a subject of intense research with useful applications, this is somewhat disappointing. The last three chapters covers probability and statistics and numerical analysis, and given the growing use of PDL in astrophysics and other areas of science, this is a fitting way to end the book. PERL code is given for the most popular probability distributions, and also for some of the standard statistical tests. Only some rudimentary algorithms are given for calculus and data interpolation, but the discussion should prepare the reader for more advanced reading in numerical algorithms using PERL and the use of PDL.
Product Review
Written for readers with at least some Perl programming experience, Mastering Algorithms in Perl delivers a solid library of algorithms written in Perl for business and mathematical computing. From data structures to cryptography and more advanced mathematical algorithms, this book provides a worthwhile guide to extending Perl's coding capabilities.
The best thing about Mastering Algorithms in Perl is the scope at which it covers the universe of algorithms while refraining from getting bogged down in academic detail. Besides basic data structures--a lynchpin of books on algorithms--the authors provide dozens and dozens of algorithms for sorting, searching, and doing mathematical computations of all kinds. While they discuss "Big-O" notation and assume a general familiarity with math, they don't overwhelm the reader. (You can even borrow the code without needing a math degree to understand it.) The focus is on efficient, reusable Perl subroutines written and compiled by three Perl experts.
Standout chapters include extending Perl's already powerful string processing abilities, game programming, and cryptography. Generally, the authors achieve a good mix of more advanced (and less well-known) algorithms, along with the basics. Chances are you won't need to use all the dozen or so sorting algorithms presented here, but the authors include them all, just in case. As a reference and tutorial, readers can pick and choose what they need for real-world Perl development.
There hasn't been a book dedicated exclusively to Perl algorithms prior to the publication of this one. In all, Mastering Algorithms in Perl fills a useful niche by compiling a powerful library of Perl algorithms that will be useful for anyone who works with this programming language, whether in business or academic computing. --Richard Dragan
Topics covered: Perl data types, Big-O notation, data structures, queues, deques, linked lists, binary trees, sorting and searching algorithms, game and dynamic programming, sets and multisets, matrices and graphs, string matching and parsing, 2-D geometry, number systems, cryptography (including DES and RSA), probability, statistics, and numerical analysis.
From Library Journal
Perl is very similar to C in syntax, and while Perl doesn't have the speed of complied C, it has been getting much faster. It also is one of the most portable languages, available for most hardware with no changes in code. It is free, which makes it very attractive to developers. This guide covers everything from data structures, sorting and searching, to sets and matrices, to cryptography, probability, and statistics. Readers must already know Perl, so this is recommended for advanced programming collections.
Copyright 1999 Reed business Information, Inc.
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