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On Computational Feasibility
Maybe the most important book you will ever readThis book will open your eyes. If you work in the field, you'll never think about your livelihood the same way again.
If you take only one thing away from this book, remember this: don't blindly trust what the advocates of the latest methodology are saying, whether it be OO, XP, RUP, or UML, without some substantive evaluative research backing them up. Glass makes compelling arguments as to why the software industry has fallen easy prey to the hucksters and snake-oil salesmen.
Insightful To The New Manager/Team Leader

My Bible
piercing!!!
A masterpiece

The Flight of a Lifetime
An Incredible Story!
A True Talent!

just plain beautiful
StunningI saw Mapplethorpe's famous exhibition in Philadelphia just before he died,the exhibit that was banned at the Corcoran in D.C., then siezed for a while in Cincinnati. The flower photographs were dye-transfer prints, which made the colour surprisingly intense; some were almost 3' tall. People would stand for a long time in front of those, enraptured, sensing the work on several different levels at once. This book does a good job of bringing that to you. You can look at this book over and over again, put in on a coffe table to start converstaions or, after having not seen it for a while, rediscover it to be awed and inspired anew once again.
The edition I have is a 1990 paperback 12" in height; the pictures are presented one to a spread, so that there is a blank white page accross from the flower, which is a very classy touch, completely the correct way to do it.
Perpetual Spring Provides Creative Inspiration!I took a course of creativity from author Dan Wakefield a number of years ago. One of the many excellent exercises we did was to take a flower and write as much as we could about what we observed during an hour. At the end of the time, I was bursting with new ideas for all kinds of things. Try it sometime!
Seeing this marvelous book by Robert Mapplethorpe (that would earn a G rating if it were a motion picture) reminded me of that exercise. I had the same feeling as I examined each image, and had a great desire to start taking notes.
The essay, A Final Flower, by Patti Smith helps put these great works in perspective. Mr. Mapplethorpe found it "as easy to hurl beauty as anything else." "He came, in time, to embrace the flower as the embodiment of all the contradictions reveling within [him]." He was inspired by "their sleekness, their fullness, Humble narcissus, Passionate zen." As such, he found flowers to be "worthy conspirators in the courting and development of conflicting emotions."
The images themselves evoke more complicated views than any others of flowers that I have seen. The closest to his style is that which Georgia O'Keeffe used in her painings. But there are more dimensions to these photographs.
For example, a single flower may evoke a part of a human body, but it will also stimulate an impression of a human emotion contained in the flower image separate from the body part. Further, the shadowed background behind the flower will add movement and context that greatly expand the meaning of the overall image. Mr. Mapplethorpe also displays a genius for using varieties of color together to express complicated rhythms that make looking at the images a lot like listening to a drum beating a distinctive tattoo. He also employs juxtaposition (to make one thing appear to be part of something else), allusions to emerging and receding, and contrasts to great effect.
The technical quality of the images is superb. The lighting, detail, and composition of each image are precisely as must have been intended. Each image is an exquisite gem. Although I liked all of the images, some appealed to me more than others. Here are my favorites:
Irises, 1988; Rose, 1989; Orchid, 1977; White Longstem Flower, 1982; Orchids, 1982; Orchid, 1986; Flowers in a Vase, 1985; Orchids, 1987; and Poppy, 1988 (second one). I would like to specially praise the astonishing Calla Lilies (1985-1988) for their amazing beauty and inspiring qualities.
Where else can something simple display so much important meaning and complexity about nature and the viewer? I suggest that you consider looking at leaves, rocks, and feathers as possible additional sources of inspiration. Try your hand at arranging tableaux that use the vocabulary of Mr. Mapplethorpe's work here.
May your heart and mind be suffused with the wonders around you . . . creating a meditation inspired by nature!


Bye-bye Let's Go, Hello FootprintSome of the telephone numbers were slightly off, but that is par for the course in India. The correct numbers were easily located via directory assistance, which the book informed us of.
We stayed at two of the highly recommended hotels between US$5 and US$6 a piece and were delighted by the overall quality and cleanliness we found.
Its descriptions of some of the sights surpassed even that of our tour guide.
We liked this guide so much that we now use Footprint guides for our travels wherever they are available and up to date.
WARNING: The guide warns that the prices for many tourist attractions will go up on Jan 1, 2001. They actually went up on October 18, 2000. Now at most major tourist sites in India, foreigners pay the same number of dollars as Indian's pay rupees.
Could not be better
A thoroughly well-researched guide.

Summer in Clearfield
Full of wonderful memories
Thank you

The Garfield Friends!
The Garfield Secrecy
I've Got a Secret!

Susan Foe, who wrote the introduction and edited the book
The greatest way to learn the phylosophy behind the movementEach sentence is a lesson in itself. While some are easy to understand, others will not be so clear in the beginning. I am sure that you will read this book more than once, reflecting on the movements and thoughts behind each form.
I recommend this books to any Tai Chi practitioner who wishes to understand the roots of the discipline.
A great introduction to tai chi theory

baby steps
Directing and Focusing Development
Must Read On Urban Sprawl

Wonderful investigative piece
Exhaustive investigation of corruption in the NHL.Conway methodically documents the path Eagelson traveled in his rise from virtual unknown to head of the NHLPA and major sports agent. How one man can succeed in an environment of obvious conflicts of interest is testimony to the ruthlessness of major sports team ownership and the naivete of the young professional athlete. Conway brings the reader to 1996 and the Eagelson indictments in US Feredal Courts in Boston but unfortunately is unable to report on the successful extradition of Eagelson to the US from Canadan proving money has its benefits.
This is a well researched book on the corruption of major sports in Norht America. Conway deserves praise for exposing the cold and calculating Eagelson who profited from the agony and injury of players he represented as agent and NHLPA head. Anyone interested in major sports off the field will be amazed by this book
A must-read book
But my specific interest revolves around writing software in large engineering (hard engineering) companies, in that very peculiar environment. Specifically, the hard engineering environment in which knowledge of the programming language is considered the most advanced software theory needed to produce a product, and in which Electrical Engineers without any formal education in advanced data structures, algorithms to manipulate them, search strategies, and heuristics are writing most of the code.
I am seeing HUGE software projects fall FAR short of their schedulled goals, because those doing the coding have simply used up all their computational cycles (I'm talking about real-time software). In these situations, managers seem to imply
1. they were blindsided
2. there are no ways to forsee such computational box canyons
3. no one could have done better, anyway.
On all 3 points, managers are wrong. And the substance on which they are so badly wrong, would make for another 10 fallacies in Glass' book. For example:
Fallacy N: Hard engineers produce advanced software algorithms.
The average hard engineer is writing Freshman undergraduate code, and making basic errors in design.
Fallacy N+1: Simple code (meaning no Computer Science theory) is much more efficient than highly tailored software algorithms. Actually, it is often orders of magnitude less efficient.
Fallacy N+2: Analytical mathematical solutions are the only ones worthy of respect. Actually, with the incredibly complex problems in modern engineering, closed form mathematical solns may never be found. Many such solns are so computationally expensive, that they never could be practical solutions.
Fallacy N+3: There are no analytical methods for identifying algorithms with prohibitive computational complexity--you must just write the software and try it out. Actually, there is a whole field of C.S. that does this.
Fallacy N+4: Modern Engineering problems are unique. Actually, the tar pits of computational complexity remain pretty stable, and Artificial Intelligence has amply failed in most of them (such as the Frame problem, and Automated Reasoning). Managers are just ignorant of the tar pits.
Fallacy N+5: Next year we'll get a new processor which is 60% faster, and our problems will go away. Actually, the mathheads that keep saying this have still not figured out that the disastrous software algorithms have computational growth rates that are exponential, and linear growth in processor speed does not define a solution to this problem.
Fallacy N+6: We write modular software. Actually, "modular" to a hard engineer and "modular" to a software engineer are radically different things. I regularly see "modular" software that has no defined interface, and no behavioral contract, so does not meet even basic requirements for reuse. Glass does not address the radically different semantics given the same words, by software and hard engineers. "Algorithm" is another word with very different meanings.
Fallacy N+7: Rule-Based software will, of course, solve our problem. Actually, automated reasoning has large undecidable and intractable areas. Engineering companies are just beginning to step in this tar pit, 25 years behind Artificial Intelligence.
Fallacy N+8: Knowledge of the syntax of a computer language, is the most valuable asset in software design. Actually, this is a trivial skill, relatively. The ability to represent symbolically complex reality in code structures, and complex manipulations of those structures efficiently, is orders of magnitude more valuable. Knowledge of just language syntax leads to literalistic algorithms, which tend to be brute force.
To his credit, Glass did mention...
Fallacy: Real-time code optimizers will fix any slowness in execution. Actually, you may gain 10-18% in speed this way, but these failing projects are orders of magnitude slower then needed. Better get rid of the real-time optimizers, and hire highly educated software designers.
I REALLY, REALLY appreciate Glass. But someone with a modern Masters degree in C.S. would realize that there is no reason to be blind-sided by most of these software disasters, and there are proven ways of evaluating these risks of failure while still in the design stage. Most VERY VERY bright hard engineers don't have the basic theory to detect computational risk, and don't even know where they should acquire it, if they wanted to improve their software algorithm design ability.
The problem is not just that (as Glass mentions) managers of software projects are out of touch with the technical people who write software. The disconnect is rather worse: most of the people who write software in big engineering companies are hard engineers, with no theoretical background in software algorithm design. There is an unspoken "amateur ethic" which condemns formal design theory. Technical leads of these "programmers" are often as uneducated, and could not identify sound software designs if their career depended on it. (So they are continually promoting Public Relations designs, and being blind-sided by failures.)
The situation in software design in America remains "tragic," and anti-intellectual, and the amateur (KISS) ethic continues to produce software projects which are computationally orders of magnitude outside of feasibility. Process does not begin to address this problem (Glass alludes to this). Nor does the strategy to redouble expectations toward the 'amateur coding ethic' and stop being such a nay-sayer. The truth remains that most technical leads in engineering companies, cannot even recognize what a software design is, and have no theoretical tools to analyze computational feasibility.
I wish that someone would address this problem in basic "Facts and Fallacies" books.
Stephen Wuest, Raytheon, M.S. in C.S. and A.I., 1999.