Beautiful Code: Leading Programmers Explain How They Think (Theory in Practice (O'Reilly))
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Book Summary Information
Editor: Andy OramEditor: Greg Wilson
Edition: Paperback
Audio: English (Original Language); English (Unknown); English (Published)
Format: Illustrated
Published: 2007-06-26
ISBN: 0596510047
Number of pages: 618
Publisher: O'Reilly Media, Inc.
Book Reviews of Beautiful Code: Leading Programmers Explain How They Think (Theory in Practice (O'Reilly))
Book Review: It ain't all that beautiful...
Summary: 2 Stars
The editors of this uneven book give us 33 chapters from various, often well-known developers, in which these developers describe some code and explain why they think that it is beautiful. There are some gems, but it's not light reading and quite a bit of it is a real slog. If you are a professional programmer, it's probably worth the effort, but otherwise I'd steer clear.
And, in fact, all too much of the code is downright ugly. This starts, sadly enough, with the first example, by Brian Kernighan, describing a limited-capacity regular expression matcher.
Yes, THAT Brian Kernighan, a software god among men. But the example he describes as beautiful would be the last thing I would ever want in any software that I had to maintain. I am sure it is efficient, and it probably works, but the only beauty that I can see is that, if you convince yourself you understand why it works, you've also proven to yourself that your mental abilities put you in an elite category of coder. God help you if you need to modify the method's functionality or (shudder) debug it.
Another dubious entry in the book is by Adam Kolawa, who describes the CERN mathematical library. He claims that no library routine can be beautiful if it uses dynamic memory allocation. The software architecture he deems beautiful passes working memory, in the form of an array to the library routines, which in turn pass it on to their subroutines. In fact, the space used by the input parameters is reused to hold the solution. I am sure that CERN math library is an excellent package, but I would hate to have the job of tracking down bugs in a system in which all the subroutines in the stack were writing back into the same array.
Software ugliness can take many forms, as, for example, in the chapter by Ronald Mak, describing NASA software used for the Mars Rover mission. The solution for a highly reliable, long running, independent system? SOA, using Java 2 and J2EE EJBs. I am a big fan of Java and J2EE, but why on earth (or Mars!) would the Mars Rover system need EJBs? The SOA and EJB technology is at its best when coupling diverse databases and interacting with legacy systems. It brings with it a significant complexity and overhead. Why would anyone think this was appropriate for the Mars Rover?
For my taste, the worst of the worst was an article by R. Kent Dybvig, describing a program for analyzing code and detecting parameter name clashes. The code to be analyzed is in Scheme, a Lisp dialect. It's been awhile since I've fooled with LISP, but I was ready to give it a try. So here is an example of a macro that has potential scope issues, if there is a bound variable t elsewhere in the code:
(or e1 e2) -> (let ([t e1]) (if t t e2))
...and here is the refactored code, in which the problem is fixed:
(or e1 e2) -> (let [g e1] (if g g e2))
I stared dumbly at this for all too long a time until I read the next phrase, "in which 'g' is a generated (fresh) identifier". Here I'd fault the author for a really rotten presentation, and also for begging the question, since the whole problem he is purporting to solve is avoiding name clashes.
In fairness, the book also has many descriptions of genuinely beautiful code. I especially enjoyed the article by Charles Petzold on efficient image processing through code generated on-the-fly. Also, Henry Warren essay on devising efficient algorithms for counting the number of enabled bits in a bit string is fascinating. Yet another stimulating article is by Brian Hayes, who describes an efficient approach for determining if three points are co-linear. This article also uses LISP as the example language, but unlike Dybvig's piece, it's clear, and "porting" the approach to Java or C++ would be straight-forward.
In summary, "Beautiful Code" is a very mixed bag. On balance, it is probably worth reading, but without doubt it is a disappointment.
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