Donald E. Knuth
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Subjects -> Computers & Internet -> Hardware -> Microprocessors & System Design -> Computer Design
Subjects -> Computers & Internet -> Programming -> Algorithms -> General
Subjects -> Computers & Internet -> Programming -> Algorithms -> General AAS
Customer Reviews:
Total reviews: 5
Average rating: 4.5 of 5
Not as Approachable as Knuth's Other Writings 3 out of 5 stars.
11 of 15 people found this review helpful.
To a reader interested in the analysis of algorithms, this book doubtlessly contains a number of very thorough analyses, with some interesting correspondence about the origin of complexity O()-notation and the term "NP-hard" thrown in.As a reader more interested in Knuth's work in general, I must admit that, despite having advanced degrees in CS and a quite decent math education, I found myself unable to follow the heavy mathematics employed, and ultimately, the problems analyzed were not interesting enough to me to make me spend the effort to follow it. One of the chapters was titled "A Trivial Algorithm Whose Analysis Isn't", and this probably sums up why I'm not entirely enthusiastic about this book and about the field of algorithm analysis in general.
Knuth wouldn't be Knuth if he didn't throw some lighter material in as well, and chapter 2, "The Dangers of Computer Science Theory", was quite amusing.
Editorial Review:
Donald Knuth's influence in computer science ranges from the invention of methods for translating and defining programming languages to the creation of the TeX and METAFONT systems for desktop publishing. His award-winning textbooks have become classics; his scientific papers are widely referenced and stand as milestones of development over a wide range of topics. The present volume, which is the fourth in a series of his collected works, is devoted to an important subfield of Computer Science that Knuth founded in the 1960s and still considers his main life's work. This field, to which he gave the name Analysis of Algorithms, deals with quantitative studies of computer techniques, leading to methods for understanding and predicting the efficiency of computer programs. More than 30 of the papers that helped to shape this field are reprinted and updated in the present collection, together with historical material that has not previously been published.