The Visualization Toolkit: An Object-Oriented Approach to 3-D Graphics (2nd Edition) Review

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The Visualization Toolkit: An Object-Oriented Approach to 3-D Graphics (2nd Edition) ReviewThis book is poorly titled, because it discusses the algorithms and techniques of visualization much more than the use of the Visualization Toolkit software. However, it is a good introduction to scientific visualization, and the free software included on the CD is an extremely powerful and useful tool. However, if you only wish to learn to use the software, The Visualization Toolkit User's Guide would be much more appropriate for you.The Visualization Toolkit: An Object-Oriented Approach to 3-D Graphics (2nd Edition) Overview95469-3 All you need to build state-of-the-art 3D visualization applications! From weather maps to MRIs, from marketing to finance, 3D visualization technology is revolutionizing the way information is delivered. And the revolution has just begun. Breakthrough tools like the Visualization Toolkit (vtk) Release 2.0 make visualization more practical and powerful than ever. This book delivers all you need to start building your own visualization applications: A complete introduction to visualization architectures and image processing algorithms-including essential algorithms for contouring, surface smoothing, cutting, slicing, decimation, and Delaunay triangulation:*An extensive collection of real-world case studies. *A working architecture and software design techniques for applying visualization to business and technical problems. *The complete vtk Release 2.0 software tools-complete C++ class libraries and source code for visualization, plus Tcl-based prototyping libraries and Java bindings...all the software you need for Win95/NT, Solaris, HP-UX, Digital UNIX, and IBM AIX!Learn how to leverage the power of vtk 2.0 to:*Build Web-based 3D visualization applications that take advantage of VRML, Java and Java3D.*Use volume rendering, which allows you to "see into" 3D datasets. *Use vtk's new 2D imaging pipeline to manipulate, display and combine 2D images into 3D datasets for further processing-and much more.Advanced 3D visualization is now practical in an unprecedented range of applications. If you're a C++, Java or Tcl/Tk programmer, you need to understand these tools and technologies. Now's the time - and there's no better place to start than The Visualization Toolkit.

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Network Processors : Architectures, Protocols and Platforms (Telecom Engineering) Review

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Network Processors : Architectures, Protocols and Platforms (Telecom Engineering) ReviewI read 'Network Processors' to learn more about this relatively new technology that is changing the way network security appliances are designed and deployed. Panos Lekkas' work seemed like the only book available that presented a broad, multi-vendor sweep of the network processor landscape. While the book has plenty of information to offer, I found it did not really live up to my expectations.
Network processors are specialized computing chips built for high performance packet processing applications. I hoped 'Network Processors' would spend a good amount of time making the case for this technology, explaining why NPs are indispensable compared to general purpose CPUs. Unfortunately, I felt the book did not make a compelling case. Chapter 2, titled 'Network Processors: Justification,' is only 10 pages, with a single chart graphing bandwidth demand vs time. I would have liked to see head-to-head comparisons of NPs against CPUs for various network applications. The book spends a lot of time discussing technologies and concepts at the periphery of NPs; I think some of that space could have been put to better use.
Here is an example of why I felt let down by this book. In the preface, the author seems to assure the reader that he will answer questions others tend to ignore. On p. xix the author writes 'In numerous industry discussions, I have encountered experienced software engineers who have implemented cutting-edge protocols, but have no idea what concepts such as scheduling, backpressure, switching fabrics, and classification mean.' To be fair, the author does explain switching fabrics and classification. However, he says almost nothing about backpressure, and he certainly never explicitly defines it; the only mention is on p. 274.
Elsewhere, I thought the book was unnecessarily confusing. It's fine to cover deep technical details, but it helps to start with clear general definitions and progress to more difficult material. The following excerpt from p. 220, the second page of chapter 12, serves as part of the 'introduction' to content addressable memory: 'The principle of associative memory is based on the inverse mechanism of establishing a relationship between the input and a specific piece of information stored in the memory array.' This sentence is fine if the reader knows what 'associative memory' is, understands the 'inverse mechanism,' and can relate to 'the input' and a 'memory array.'
The layout of the book itself may have contributed to my difficulty with it. The font is one of the smallest I have ever encountered. The footnotes are so small as to be almost illegible. I like the hardcover binding, though.
Although not the author's fault, readers should be aware that many of the companies and some of the technologies in 'Network Processors' have disappeared. Each time I encountered a new company or product I checked to see if their Web page or product line still existed. For example, IBM's PowerNP receives an entire chapter; it was sold to Hifn in January 2004. In many cases, however, surviving vendors have not brought too many products to market since the book's late 2002 publication date.
I believe a second edition of 'Network Processors' would benefit from an editor who challenges the author to be more organized and generous with his audience. The book was built on a good idea -- bringing knowledge of NPs to general readers. A second edition should ensure that goal is met, since we do need to know more about this promising technology.Network Processors : Architectures, Protocols and Platforms (Telecom Engineering) OverviewNetwork processing units (NPUs) will be the occasion of sweeping changes in the network hardware industry over the next few years. This new breed of microchip impacts chip designers like Intel, equipment vendors like Cisco, application developers like IBM and Morotola, and an army of software engineers who spent the last decade working on protocols and network management solutions. A thoroughly practical dissection of the early NPU market, this designer's guide explains how network processors work and provides detailed information on all major commercial architectures, from features to design considerations. Comparative tables are a rich source of cross-industry info. Coverage includes traffic managers, classification chips, content-addressable memories, switch fabrics, security accelerators, storage coprocessors and NetASICs.

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Distributed Systems for System Architects (Advances in Distributed Computing and Middleware, Volume 1) Review

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Distributed Systems for System Architects (Advances in Distributed Computing and Middleware, Volume 1) ReviewThis is quite an interesiting and thourough book. Although I really don't understand the stupidity of it's price since I bought it for 60 Euro in Portugal... Really, You can get all the information in this book for much less than this absurd price....Distributed Systems for System Architects (Advances in Distributed Computing and Middleware, Volume 1) OverviewThe distributed systems architect assembles pieces of hardwarethat are at least as large as a computer or a network router, andassigns pieces of software that are self-contained - such asJava applets - to those hardware components. As systemcomplexity, size and diversity grow, the probability of inconsistency,unreliability, non-responsiveness and insecurity, increases. It isabsolutely necessary for distributed systems architects to understandthe management of such complex systems. Distributed Systems forSystem Architects addresses these issues.

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Randomized Algorithms Review

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Randomized Algorithms ReviewThis book is a jewel. It demonstrates how clever and beautifully simple probabilistic ideas can lead to the design of very efficient algorithms. I like its very verbal intuitive style,
with proof strategies being always transparently explained.
For computer scientists, this is *the* reference work in randomized algorithms, by now a major paradigm of algorithms design. For classical probabilists, this
could serve as an eye-opener on unsuspected applications of their field to important areas of computer science.Randomized Algorithms OverviewFor many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This book introduces the basic concepts in the design and analysis of randomized algorithms. The first part of the text presents basic tools such as probability theory and probabilistic analysis that are frequently used in algorithmic applications. Algorithmic examples are also given to illustrate the use of each tool in a concrete setting. In the second part of the book, each chapter focuses on an important area to which randomized algorithms can be applied, providing a comprehensive and representative selection of the algorithms that might be used in each of these areas. Although written primarily as a text for advanced undergraduates and graduate students, this book should also prove invaluable as a reference for professionals and researchers.

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Software Engineering: (Update) (8th Edition) Review

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Software Engineering: (Update) (8th Edition) ReviewI used this book as the text in my software engineering class in the spring semester of 2008. When I was evaluating it for potential adoption, I did not read through it in detail, I looked over the chapter titles and subtitles, read the first few chapters and examined the exercises at the end of the first few chapters. As the semester progressed, I found myself wishing I had read further into the text.
As I moved through the chapters, I found myself mentally noting over and over again that topics are repeated. When the class was over, I asked the students their opinion of the book and they were unanimous, with no prompting from me, in saying that there is a great deal of repetition after the first chapters.
I have no complaint about the quality of exposition or the coverage of software engineering in this book. My reason for not continuing to use it in future classes is solely due to my belief that the size could have been reduced from the current 840 pages to around 600 pages with no real loss of content of flow.
Software Engineering: (Update) (8th Edition) OverviewTHE most current Software Engineering text in the market– quality trusted coverage, practical case studies, strong lecturer support.

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Engineering a Compiler, Second Edition Review

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Engineering a Compiler, Second Edition ReviewThis is really a super compiler text. It is also one of the most recent compiler books you can buy.
First of all this is a theoretical book. If you read the title 'Engineering a compiler' as 'Coding/Building a compiler' you would be disappointed! So, if you're looking for a learing-by-coding book, this is not for you (but I have some recommendations at the end of this review in the latest paragraph). The difference with most of the other theoretical books is that this book is not a dry text. It has also a nice layout. It gives plenty of examples, and all topics are well connected to each other. It's a pleasure to read for not native English people, so native English people can read it pretty fast.
This book read like a novel.. It does contain enough diagrams, tables, etc. but not too much (crowded), and everything is well explained.
You can read this book as a compiler introduction book. But I can only recommend this to B.Sc/M.Sc Computer Science students (like me). You don't need to have a M.Sc in Mathematics to understand this text, (all the math, eg. liveness graphs are well explained), but you will understand everything better if you have some background in algorithms (design), pseudocode, etc. like you gained during your B.Sc program. People without formal computer science education I would recommend to read a practical book first (see at the end of this review), because you may find else this text too theoretical.
This book focus on code optimizations. According to the authors (and me) compiler front ends (scanning/parsing/etc) are commodities today, and the backend (codegeneration) is where the difference is made nowadays. So if you're looking for a introduction text into compiler optimization this book is for you!
If you're looking for a more practical book I advice you to read 'Programming Language Processors in Java' from Watt & Brown. In that book you learn to build a nice stack virtual machine in Java with 'advanced features' like records (structs), procedures/functions, arrays and so on. That book is a good companion for 'Engineering a Compiler' to give you some practical insight. If you're looking for a Language Design book I advice you to look at 'Programming Language Pragmatics'. Both books are worth the money...Engineering a Compiler, Second Edition Overview

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Concepts, Techniques, and Models of Computer Programming Review

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Concepts, Techniques, and Models of Computer Programming ReviewThis book is a real mind-bender that illuminates paths for computer design at both the conceptual and practical levels I'd never travelled down before.
The notion that one language can be so flexible as to accomodate both the syntax and semantics of so many different computational models, or paradigms, took some unlearning of bad programming practice before its power, elegance and potential began to sink in.
It also explodes the myth that "pure" languages -- i.e., pure OO, or pure functional, etc., languages--have some kind of innate advantage over so-called "hybrid" languages. In fact, "hybrid" (or as the authors would prefer to call them, "multi-paradigm") languages come out of this book looking even more powerful than the "pure" ones, insofar as they allow the programmer to use the right model for each task, instead of trying to make OO fit, for instance, in places where it doesn't fit so well.
The idea here is that each computational model represents a completely different way of approaching a domain problem. Used by themselves, each has its niche. For instance, everybody knows OO is good for domain modelling and busines objects. Prolog-type languages are good for applications that need to apply rules over a set of data. Functional languages are great in mathematical applications. And so on. What is new here is that one can program in an environment in which all of these tools are available in a single core semantics that seamlessly weaves these computational models into a complementary whole. Used together judiciously, with an eye toward program correctness, they make things possible that have long been considered very hard -- for instance, constraint programming.
Mozart-Oz, the underlying technology, is a strange language when you first look at it. It's hard at first to get used to concepts like "higher-order programming" or "by need execution" or "lazy execution" if you are the programming grunt in the field of most modern IT shops, forced by bosses to code in your standard fare -- Java, C#, VB, etc. If OO in Java is like the hammer that makes everything look like a nail, in Mozart-Oz you have a language that is like walking into Ace hardware store, a swiss army knife of a language (conceptually speaking) that challenges you to become a highly skill code craftsman, not just a programmer.
But, if only for the personal growth you will experience grappling with the concepts in this book, I recommend it very highly even to "non academic" programmers (like myself) as well as to any advanced student of computer science. It may be painful, you may scratch your head in places where the concepts just seemed to leap over your cranium, but if you are patient, do the exercises (and at least think about what it would take to tackle some of the research projects), you will grow.
Unfortunately, you may find the languages you work on to be rather confining, and maybe even boring, after you get a whiff of what multi-paradigm programming can do. More likely, however, is that you will grasp very clearly how the language you code in today works, and that can only make you a better software engineer. So do it-buy this book!Concepts, Techniques, and Models of Computer Programming OverviewThis innovative text presents computer programming as a unifieddiscipline in a way that is both practical and scientifically sound. The bookfocuses on techniques of lasting value and explains them precisely in terms of asimple abstract machine. The book presents all major programming paradigms in auniform framework that shows their deep relationships and how and where to use themtogether.After an introduction to programming concepts, the book presents bothwell-known and lesser-known computation models ("programming paradigms"). Each modelhas its own set of techniques and each is included on the basis of its usefulness inpractice. The general models include declarative programming, declarativeconcurrency, message-passing concurrency, explicit state, object-orientedprogramming, shared-state concurrency, and relational programming. Specializedmodels include graphical user interface programming, distributed programming, andconstraint programming. Each model is based on its kernel language -- a simple corelanguage that consists of a small number of programmer- significant elements. Thekernel languages are introduced progressively, adding concepts one by one, thusshowing the deep relationships between different models. The kernel languages aredefined precisely in terms of a simple abstract machine. Because a wide variety oflanguages and programming paradigms can be modeled by a small set of closely relatedkernel languages, this approach allows programmer and student to grasp theunderlying unity of programming. The book has many program fragments and exercises,all of which can be run on the Mozart Programming System, an Open Source softwarepackage that features an interactive incremental development environment.

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Handbook of Applied Optimization Review

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Handbook of Applied Optimization ReviewThis massive book is the best compilation on optimization algorithms I've seen so far. All chapters are authoritatively written and up to date. A great job by the editors, Dr. Pardalos (one of the greatest authorities in Combinatorial Optimization) and Dr. Resende (the creator of GRASP).Handbook of Applied Optimization OverviewOptimization is an essential tool in every project in every large-scale organization, whether in business, industry, engineering, and science. In recent years, algorithmic advances and software and hardware improvements have given managers a powerful framework for making key decisions about everything from production planning to scheduling distribution.This comprehensive resource brings together in one volume the major advances in the field. Distinguished contributors focus on the algorithmic and computational aspects of optimization, particularly the most recent methods for solving a wide range of decision-making problems.The book is divided into three main sections: algorithms, covering every type of programming; applications, where computational tools are put to work solving tasks in planning, production, distribution, scheduling and other decisions in project management; and software, a comprehensive introduction to languages and systems.Designed as a practical resource for programmers and project planners and managers, it covers optimization problems in a wide range of settings, from the airline and aerospace industries to telecommunications, finance, health systems, biomedicine, and engineering.

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Genetic Programming: An Introduction (The Morgan Kaufmann Series in Artificial Intelligence) Review

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Genetic Programming: An Introduction (The Morgan Kaufmann Series in Artificial Intelligence) ReviewThis book is a great introduction to genetic programming and should be a model for textbook authors in other fields. Knowing little about genetic programming to begin with, this book guides the reader through the various topics and problems associated with genetic programming in a very logical and understandable way. Highly recommended! I wish more technical books were like this!Genetic Programming: An Introduction (The Morgan Kaufmann Series in Artificial Intelligence) Overview

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Handbook of Statistical Analysis and Data Mining Applications Review

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Handbook of Statistical Analysis and Data Mining Applications ReviewThe "Handbook of Statistical Analysis & Data Mining Applications" is the finest book I have seen on the subject. It is not only a beautifully crafted book, with numerous color graphs, chart, tables, and screen shots, but the statistical discussion is both clear and comprehensive.
The text does not use only one statistical data mining application to display examples, but provides a rather thorough training in the use of both SAS-Enterprise Miner and STATISTICA Data Miner. A section on SPSS Clementine is also provided, giving comparisons between the various packages. Also employed are STATISTICA's C&RT, CHAID, MARSpline, and other data mining and graphical analytic tools.
The text does not burden the typical data mining researcher with the internals of how the various tools work. It is therefore not steeped in equations. Some are to be found, of course, but the emphasis is on understanding the concepts involved and on how to apply these concepts to real data - which is provided to the reader in terms of data tutorials. Specialized datasets have been prepared by both authors and outside experts in various areas of inquiry ranging from entertainment, financial, engineering, clinical psychology, dentistry, demographics, medical informatics, meteorology, astronomy, and more. Each tutorial is associated with data stored on either the associated CD that comes with the book, or which can be downloaded from a companion web site. Worked out examples of how to use data mining techniques on such data is provided to help the reader gain a solid feel for the data mining enterprise. The final third of the book is devoted to a partial selection of the available tutorials. The two earlier chapters demonstrate how to use data mining software for the analysis of data.
I highly recommend this work to anyone having an interest in data mining. I might also add that the Amazon price of $72.37 is truly excellent for an 864 page academic text, having full color tables and screen shots on some one-third of the pages, plus a CD. A bargain indeed.
Handbook of Statistical Analysis and Data Mining Applications OverviewThe Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions.

Written "By Practitioners for Practitioners"
Non-technical explanations build understanding without jargon and equations
Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models using Statistica, SAS and SPSS software
Practical advice from successful real-world implementations
Includes extensive case studies, examples, MS PowerPoint slides and datasets
CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book


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Garbage Collection: Algorithms for Automatic Dynamic Memory Management Review

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Garbage Collection: Algorithms for Automatic Dynamic Memory Management ReviewGarbage collection is a very interesting and complicated topic. To understand different garbage collection algorithms, one has to go through various research papers published over last 30 years or read the simplified descriptions presented in Java site and Bill Venners artima.com. This book does an excellent job in putting together all these algorithms in a logical order that gives us a chance to understand the different challenges sceintists and programming language authors faced and how the algorithms evolved over the time. The book starts with basic overview and history of commonly known algorithms: Reference counting, Mark and Sweep, and Copying algorithms. It then elaborates each of these algorithms, enumerates their pros and cons, and presents imporvements done by different researchers. After this, the book moves on to advanced algorithms like Generational algorithm and concurrent mark and sweep algorithm. I recommend this book to anyone interested in garbage collection. I haven't seen any other book on this topic. Even for programmers who mostly don't have to worry about GC as it is "automatically" done, this is a good book to understand and appreciate what goes on behind the scenes. Also, knowledge of the concepts in this book will be invaluable in performance tuning.Garbage Collection: Algorithms for Automatic Dynamic Memory Management OverviewModern software places increasing reliance on dynamic memory allocation, but its direct management is not only notoriously error-prone. Garbage collection eliminates many of these bugs. This reference presents each of the most important algorithms in detail, often with illustrations of its characteristic features and animations of its use.

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Compilers: Principles, Techniques, and Tools Review

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Compilers: Principles, Techniques, and Tools ReviewDuring each compiler stage (lexical analysis, syntax analysis, translation, type checking, translation, code generation, and code optimization) multiple methods, strategies, and algorithms are presented. This comprehensive book examines items that are unique to the various languages presented (Fortran, C, and Pascal); there are even sections on dealing with estimation of types (10.12) and symbolic debugging of optimized code (10.13). Wow! The exercises are thorough, challenging, and thought provoking. Examples are interleaved with the discussion and algorithms. There is an excellent set of historical and bibliographic information at the end of each chapter. The use of automated tools such as lex, yacc, and compiler-generators is discussed throughout the text. This is an advanced book, however a good understanding of compilers can be obtained without understanding the details of every algorithm.Compilers: Principles, Techniques, and Tools OverviewThis introduction to compilers is the direct descendant of the well-known book by Aho and Ullman, Principles of Compiler Design. The authors present updated coverage of compilers based on research and techniques that have been developed in the field over the past few years. The book provides a thorough introduction to compiler design and covers topics such as context-free grammars, fine state machines, and syntax-directed translation. 0201100886B04062001

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Compilers: Principles, Techniques, and Tools (2nd Edition) Review

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Compilers: Principles, Techniques, and Tools (2nd Edition) ReviewI spent some serious quality time with the first edition (the "red dragon book"), in three main episodes over the past dozen years: 1) undergraduate compilers class, 2) industry project, and 3) parser generator implementation. During all three episodes, I was disappointed in various ways, though there is no denying that the book contains a wealth of information. As an undergraduate, I found the book somewhat impenetrable. When in industry, I found the book too abstract. When implementing a parser generator, I discovered that the book excludes important research results with regard to LR parser generation. It is the last disappointment that I will focus on.
The book presents parser generation in layers of increasing complexity, from SLR to LR to LALR, where LALR is presented as the penultimate algorithm, though LALR parsers can only handle a subset of the grammars that LR can handle. The justification for this is that the original Knuth LR algorithm is intractable for large grammars. However, an efficient, fully correct, approach for LR parser generation was published in 1977, and on top of that it appears easier to implement than efficient LALR parser generation! The red dragon book's original authors simply cannot have been unaware of this research result, but I suspect that they elected to warm over the "green dragon book" (published in 1977) rather than incorporate the state of the art as of 1986 into the "red dragon book". Now here we are another 20 years later, and as near as I can tell from reading through available online information, the "purple dragon book" is perpetuating this omission. The result of the red dragon book is that we have an entire generation of computer scientists who have been mislead to think that LALR is somehow superior to LR, and the purple dragon book is setting things up for yet another generation to be mislead.Compilers: Principles, Techniques, and Tools (2nd Edition) OverviewCompilers: Principles, Techniques and Tools, known to professors, students, and developers worldwide as the "Dragon Book," is available in a new edition. Every chapter has been completely revised to reflect developments in software engineering, programming languages, and computer architecture that have occurred since 1986, when the last edition published. The authors, recognizing that few readers will ever go on to construct a compiler, retain their focus on the broader set of problems faced in software design and software development.

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Numerical Methods, Algorithms and Tools in C# Review

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Numerical Methods, Algorithms and Tools in C# Review-In code, bottom page 16, "var" should be "var2"
-In code, top of page 17, uses "int, i, j" in an example about "string, x, y"
-in text, page 18, "...the variable i can accept a all the values"
-in code, page 19, missing quotation marks
-in code, page 22, "In32" should be "Int32"
-in code, page 23, uses "i" and "I" interchangeably (case matters in c#)
-in code, page 32, "intefaces" should be "interfaces"
-in text, page 57, "The latter contains contains interfaces..."
These errors aren't even all the errors in chapter 1, let alone the rest of the book.
This lack of attention to detail is inexcusable. This book must have been rushed to meet a deadline. It should not have been published in its current state. Do not purchase this edition of this book. The book's purpose is to solve complex mathematical problems through C# programming - but its coded examples often will not compile due to these careless mistakes.
If the author was not able to catch these simple mistakes, I do not trust his ability to avoid mistakes in the more complex areas.Numerical Methods, Algorithms and Tools in C# OverviewComprehensive Coverage of the New, Easy-to-Learn C#Although C, C++, Java, and Fortran are well-established programming languages, the relatively new C# is much easier to use for solving complex scientific and engineering problems. Numerical Methods, Algorithms and Tools in C# presents a broad collection of practical, ready-to-use mathematical routines employing the exciting, easy-to-learn C# programming language from Microsoft.The book focuses on standard numerical methods, novel object-oriented techniques, and the latest Microsoft .NET programming environment. It covers complex number functions, data sorting and searching algorithms, bit manipulation, interpolation methods, numerical manipulation of linear algebraic equations, and numerical methods for calculating approximate solutions of non-linear equations. The author discusses alternative ways to obtain computer-generated pseudo-random numbers and real random numbers generated by naturally occurring physical phenomena. He also describes various methods for approximating integrals and special functions, routines for performing statistical analyses of data, and least squares and numerical curve fitting methods for analyzing experimental data, along with numerical methods for solving ordinary and partial differential equations. The final chapter offers optimization methods for the minimization or maximization of functions.Exploiting the useful features of C#, this book shows how to write efficient, mathematically intense object-oriented computer programs. The vast array of practical examples presented can be easily customized and implemented to solve complex engineering and scientific problems typically found in real-world computer applications.

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