Computer Science Books

we were using this book at gatech. I had two courses with him and I have learned a lot from Mr. "Samurai Professor"! God bless him!

The book is very good and covers CMOS circuits in great details. It includes very good expanation diagrams. It covers not only basic static cmos family but also new cmos family circuits.

It is meant for digital CMOS circuit designers. Not meant for digital circuits level. All are at CMOS transistor level analysis and design. Usually, most of the digital CMOS circuits in the industry have already been laid out and kept as part of the standard cell library. Even though so, we still need to have a strong concept on digital CMOS circuits in order to be a good IC designer.

It is a very good book for the beginner and intermediate level, for those who has the interest to pick up CMOS digital circuits. The book is not meant to help the reader to be good at layouts, semiconductor physics and CAD tools. There are other books for those fields. The book presents a thorough explanation on digital CMOS circuit operation using both equations and words. A lot of diagrams and graphs/curves. That makes it very useful for self study. Helps the beginner (what i meant by "beginner" is that he/she should have a knowledge in fundamentals of semiconductor physics such as pn junction) to grasp the concept of digital CMOS circuit well.

I have 2 more books that are by Leblibici (CMOS Digital Integrated Circuits Analysis & Design) and Neil Weste (Princple of CMOS vlsi design) and I found that this is better than both the books for beginners and for CMOS purpose. But the book by Weste is a very good reference, not meant for self reading unless you have a good foundation in CMOS circuit design already. The book by Leblibici is almost as good as the one by Uyemura. So, I use Leblibici book for extra reference and would usually use the book by Uyemura for first read. Therefore, I found the book by Leblibici is just as important.

The book is excellent for teaching approximation algorithms. The book was new, but I benefit of a reduced price (probably promotional).

This book is a great sequel to Garey and Johnson. The appendix of this book gives a list of all NP optimisation problems together with their current approximability (or inapproximability results) in a Garey Johnson fashion.

Developing approximation algorithms for NP hard problems is now a very active field in Mathematical Programming and Theoretical Computer Science. There have been a number of exciting developments like semidefinite programming , the Goemans Williamson algorithm for max cut et al.

On the other hand, from a theoretical computer science point of view, we now have a proof that many of these problems cannot have polynomial approximation algorithms unless P=NP.

This book provides an excellent introduction to both areas. A worthy supplement to Garey and Johnson, Papadimitriou's books on combinatorial optimisation and computational complexity, Hochbaum's book on approximation algorithms, Alon and Spencer's book on the probabilistic method and finally Motwani and Raghavan's book on randomised algorithms.

This book is a great sequel to Garey and Johnson. The appendix of this book gives a list of all NP optimisation problems together with their current approximability (or inapproximability results) in a Garey Johnson fashion.

Developing approximation algorithms for NP hard problems is now a very active field in Mathematical Programming and Theoretical Computer Science. There have been a number of exciting developments like semidefinite programming , the Goemans Williamson algorithm for max cut et al.

On the other hand, from a theoretical computer science point of view, we now have a proof that many of these problems cannot have polynomial approximation algorithms unless P=NP.

This book provides an excellent introduction to both areas. A worthy supplement to Garey and Johnson, Papadimitriou's books on combinatorial optimisation and computational complexity, Hochbaum's book on approximation algorithms, Alon and Spencer's book on the probabilistic method and finally Motwani and Raghavan's book on randomised algorithms.

This is more advanced book for CFD (comparing with the volume I). More specifice topics were talked about in this book. It is a very good book for beginner, also a good reference.

This volume is an extremely clear summary of basic theory and comparative techniques for computational resolution of fluid mechanics problems. Code examples are clear and extremely helpful to practitioners trying to produce useful models.

The reader should be familer with the general techniques of Computaional Science. This book does an excellent review of thoes basic techniques which are basic for computational fluid dynamics. I just finished reading it and am Now starting on the second volume. I am doing a computer Simulation of Ship wakes and this book is I think nesessary reading before a researcher dives in to the mass of research papers published in this field.

This book and its author are just amazing. Konrad Zuse is definitly a unique character and so is his story of the invention of the FIRST computer during World War II in Berlin.

Zuse explains how and why he build the world's first computer. Easy to understand, but not belittling. This book is essential for anyone interested in the history of CS.

An excellent source of information for those who mistakenly thought that ENIAC was the first general purpose computer.

I'm writing about the 2nd ed. (1990), but if you landed here, I think what I have is of value for later editions too. The book is fantastic. There are a myriad of technical terms for various kinds of multivariate analyses. The average person has no idea what the names mean -- or how to choose between them! To be able to DO anything (right, anyway) you need a CONCRETE understanding. Such is what this book provides. Right off the bat, the book tells you -- not only what kind of data each technique requires -- but what questions you might ask (and want answered) for such data. So, in a mere 4 pages -- near the beginning! -- you get 1 or 2 paragraphs on each of these: factor analysis, discriminant analysis, cluster analysis, multiple linear regression, principal components analysis, and more. You'll know what these techniques require as input (what kinds of data situations) and what they assume the question(s) is/are that you want answered -- already concrete, already good understanding of the differences of the formerly cryptic technique names in a mere 4 pages! I have seen no other book do this. The rest of the book is nearly as effective in the decoding of other details of the multivariate analyses. In short, start with this book, because therein you will be way way ahead in acquiring a perspective on multivariate analyses with little effort. Go to any other book(s) first and you may eventually develope a perspective -- only by accident, that is with little author help -- after a long hard road. Get your perspective from the get-go instead -- with this book.

While this book will not teach you all you need to know about any of the techniques to be an expert, it WILL teach you enough to read research, and to learn what the various techniques do. The mathematical level is moderate, and the emphasis is on practical applications. Highly recommended for grad students in the social sciences

Often, students and researchers need to perform multivariate statistical analyses on their data. Unfortunately, a lack of mathematical training prevents many from taking advantage of advanced techniques, in part, because books focus on the theory and neglect explaining how to perform and interpret multivariate analyses on real-life data. Computer-Aided Multivariate Analysis is a welcome exception, helping students choose the appropriate analyses for their data, carry them out and interpret the results. Only a limited knowledge of statistics is assumed and geometrical and graphical explanations are used to explain what the analyses do. However the basic model is always given and assumptions are discussed. In this edition the computer emphasis is enhanced by the inclusion of three additional statistical packages written for the personal computer. The authors also discuss data entry, database management, data screening, data transformations, as well as multivariate data analysis. This third edition contains a new chapter on log-linear analysis of multi-way frequency tables.

What set this book apart from other books is that it puts side by side C++ and Fortran. Not only that, it does not waste (your) time and talks about the essentials of these two programming languages in a straightforward away. Things like how to input and output your data, arrays, logical expressions and even "arcane" sujects like pointers and objects are presented in a clear way.

Note, though, that this is an introductory book that is aimed at those that are taking their first steps in C++ and/or Fortran programming. And for an introductory book it does a fine job.

In addition to being a chemist myself who uses programming technologies extensively, I also teach courses designed to introduce relevant software technologies to other chemists, such as programming and database skills.

One of the problems that I faced was lack of a good introductory text on programming that would be relevant to an applied scientist. Most introductory programming books appear to be written for someone who intends to be a computer scientist, or even worse, rather than teaching language-independent skills, they try instead to teach you one programming language. As anyone knows who has ever browsed the computer section of their local bookstore or even here on Amazon, the number of books available on the topic of programming is enormous, to say the least.

I was pleasantly surprised when I came across this book at a local electronics store. For the time being, I am going to refer to it as a good starting point for any scientist who wishes to enhance his/her programming skills.

Barlow and Barnett cover many of the topics that I consider essential when learning any programming language, such as data types, operators, conditional statements, looping constructs, etc. Furthermore, he even covers important concepts like accessing memory (e.g. pointers in C++), state machines, abstraction, and object-oriented techniques. I was very happy to see the authors stress the importance of striving for ANSI compliant code.

For a book that was published in 1998, I was very impressed to see a section on template programming with C++. Clearly, Barlow and Barnett are very good at recognizing emerging trends. Furthermore, they are equally adept at explaining difficult concepts in a lucid way. Towards the end of the book, the authors' physics slant is evident by the section on numerical analysis, but the treatment is great, since it exemplifies how programming can be used for solving computationally intensive tasks that have physical significance.

Although this book on programming is geared towards scientists, it really would serve as a nice introduction to programming for any discipline. Although Fortran's popularity is very low outside of engineering, the juxtaposition of C++ with Fortran was a very nice touch, as it really allows one to look past language specific features in order to see generic programming concepts. Computer languages, like spoken languages, are such that, the first one is hardest to learn, but with each one you learn, the process of learning the next one becomes successively easier, and authors' use of two languages in one book really exemplifies this concept.

This book does not aim to teach you either C++ or Fortran, although it does point out some real pitfalls (e.g. in C++, x = a[i] + i++) in each language. Instead, the authors gives you a great foundation, from which you will be able learn generic programming concepts, as well as evaluate programming languages, so that in the future, you should be able to select one that is appropriate for your task at hand. Finally, they authors give great examples of using programming technologies to solve problems of a scientific nature, and he is able to accomplish in less than 300 pages what most books fail to do in three to four times that amount.

Intended for first or second year engineering or science students. It teaches programming at an introductory level. Yes, its a text book for one of those Programming 101 courses.

However, what sets this textbook apart from others is that it employs two languages (i.e. Fortran and C++), instead of one, to teach the same old material. And this has some interesting charasteristics. The authors has presented the material in a comparative way so that the student has the chance to see, very clearly, the relative merits of each language. For example, when they introduce arrays you will see the ease of Fortran in dealing with them. On the other hand, when object oriented programming is presented, C++'s superiority becomes apparent for that purpose. By seeing two languages side by side, one can also discern the fundamentals from language specific rules.

I'm familiar with Fortran and it has been a while since I took my first course in programming but this textbook has taught me quite a lot of things. If you know one of the languages, it might still make sense to buy it. You will appreciate your language better and will find what the other language does better. By the way, the book doesn't teach about mixed language programming.

This is a good book in reliability modeling of computer systems as it explicitly explains very deep knowledge in a clear way. Many technologies presented in this book are easy to be applied in practice. The examples help me clearly understand them although there are some mathematical formulas out of my current knowledge structure.

The book studies the reliability on software, hardware, network and system levels. I especially like the part about the grid reliability that can be implemented to study the reliability of large-scale systems.

This is a good book that comprehensively investigates the reliability for most advanced computer systems.

The world of information security is replete with conjecture, confusion, and outright fiction. In brilliant contrast, Bob Blakley's "CORBA Security - An Introduction to Safe Computing with Objects" stands as a testimony of precision, clarity, and truth, with one exception: the book's title.

While the volume addresses architectural aspects of CORBA Security and provides a healthy discussion of object-specific security issues, it is really about a much more pervasive subject. Namely, how the fundamental tenant of Security Policy design can and should be woven through Identity, Authentication, Privilege, and Access Control. It also tackles two of the most misunderstood, yet critical security issues in modern N-tier distributed systems: Delegation and Non-Repudiation.

The writing style, like the author himself (whom I'm acquainted with on a processional level) is modest, direct, and inclusive. All terminology is progressively defined and clearly communicates the underlying concepts. As a budding security architect and veteran software engineer I highly recommend this book to managers, system designers, security administrators, and members of the legal and causality communities. In short anyone needing a deeper understanding of policy-driven, distributed computer security systems, CORBA or no CORBA.

"CORBA Security" is very much in the classic vein of "The Elements of Style" (E.B. White) - concise, accessible, and durably relevant. A true classic!

I would highly recommend this book for organizations needing "information security (INFOSEC)" as it pertains to the Object Management Group's (OMG's) Common Object Request Broker Achitecture (CORBA) standard. The book takes a less technical overview to the OMG CORBASecurity specification and what CORBASecurity standard is trying to accomplish. It does this by using less technical jargon and acronyms which are sometimes confusing to neophytes unfamiliar with the very technical and complex world of INFOSEC.

In my view, the most important part of the book is its last chapter (i.e., Chapter 10 entitled "Questions to Ask Your Secure Object System Vendor"). Why? Because this chapter outlines thirteen questions that end user organizations can ask their vendors (in this case, Object Request Broker (ORB) vendors and referred to in the book as "secure object system vendors"). These thirteen questions are simple security questions that will get to the bottom line of capabilities of what ORB vendors may or may not supply with their ORB's security service. Thus, it can be used as a buyers guide to the types of security capabilities that your organization may desire with an ORB product.

Recent hacker attacks on such high profile sites as Amazon and Yahoo should be a slap on the side of the head style reminder as to how important security is in computing. However, while these are significant, one must not lose sight of all of the other aspects of security, which dwarfs the rather simplistic nature of these attacks. For many systems, security issues must be as integral a part of the design as which classes to use.
Despite the title, this book is not focused on CORBA, but is more a general introduction to the issues of security. In that area, it is a very good book. The basic problems and general solutions to security issues are presented in a manner well within the grasp of non-technical readers.
The three main areas of protection: authorization, accountability and availability are explained in detail, using an example that is both practical and instructive. Submitting a tax return electronically is a serious business and the explanation of how every party to the transaction satisfies these three criteria is the best explanation of the process that I have read.
If your goal is to learn the basics of computer security in the context of, but not exclusive to a CORBA environment, then this book is exactly what you are looking for. If your interest is in a detailed explanation of CORBA, then you must look elsewhere.

Everyone involved in usability needs a highlighted, or bookmarked iwth post-it notes, copy of this book. Its always powerful to back up how important usability is to others who are unfamiliar with its power, be it your team or a client, and this book shows you how to do figure out the return of investment with dollars, something everyone understands. Overall, it gets the point across by showing readers how to do it for themselves with formulas that are not all that difficult at all, and where to pull numbers from to calculate the ROI.

If you are looking for help with quantifying the cost of bad interface design and/or how poorly designed application costs the company money, then this is the book for you.

This book is practical and right on target for helping IT groups and customers understand the importance of systems that allow work to be completed efficiently. The authors do a great job quantifying the cost of poorly design, unusable system.

If you have ever tried to demonstrate to an IT group that it is more costly not to change the system, then this book will give you the strategy for showing how investing in system changes actually costs less in the short term, than in the long term.

End users will cheer anyone who applies the information in this book to the applications they use.

Bite the bullet, buy the book. in these days of cut budgets, you must be able to justify your worth. There are formulas in this book that anyone designing software or digital products can use-- not just usability geeks. IA's, designers, GUI kids... time to learn the math.

I bought this book for the math course I had taken having the same title. This is an excellent book, but only if you are really interested in its content. It's not a casual read, since it's graduate text. Also, a background in number theory will be of great help - being a CS major, I had a little tough time in the beginning, but things turned out just fine. As for content, it has excellent coverage of the subject, and I would highly recommend this as a reference in this subject. Remember, though, that this book deals COMPUTATIONAL aspects, for only number theory, look for other books like Ireland-Rosen.

This book is an excellent compilation of both the theory and pseudo-code for number theoretic algorithms. The author also takes the time to prove some of the major results as background to the algorithms, in addition to sets of exercises at the end of the book. The book is too large to do a chapter by chapter review, so instead I will list the algorithms in the book that I thought were particularly useful:

1. Most of the algorithms on elliptic curves. The author reminds the reader that number-theoretical experiments resulted in the famous Swinnerton-Dyer Conjecture and the Birch Conjecture. (a) the reduction algorithm, which for a given point in the upper half plane, gives the unique point in the half plane equivalent to this point under the action of the special linear group along with the matrix that maps these two points to each other. (b) The computation of the coefficient g2 and g3 of the Weierstrass equation of an elliptic curve. (c) The computation of the Weierstrass function and its derivative. (d) Determination of the periods of an elliptic curve over the real numbers. (e) The determination of the elliptic logarithm. (f) The reduction of a general cubic (f) The Shanks-Mestre algorithm for computing the order of an elliptic curve over a finite field F(p), where p is prime and greater than 457. (g) The reduction of an elliptic curve modulo p for p > 3. (h) The reduction of an elliptic curve modulo 2 or 3. (i) Reduction of an elliptic curve over the rational numbers. (j) Determination of the rational torsion points of an elliptic curve. (k) Computation of the Hilbert class polynomials and thus a determination of the j-function of an elliptic curve.

2. A few of the algorithms on factoring. (a) The Pollard algorithm for finding non-trivial factors of composites. (The author does not give the improved algorithm due to P. Montgomery, but does give references) (b) Shanks Square Form Factorization algorithm for finding a non-trivial factor of an odd integer. (c) Lenstra's Elliptic Curve test for compositeness.

3. Primality tests (a) The Jacobi Sum Primality Test for a positive integer. (b) Goldwasser-Killian elliptic curve test for a positive integer not equal to 1 and coprime to 6.

The author gives an overview of the computer packages used for number theory, including Pari, which was written by him and his collaborators. I have not used this package, but instead use Lydia and Mathematica for most of the number theoretic computations I need to do.

Cohen (the world renowned expert) starts with the most basic of algorithms (i.e. Euclid & Shanks). He moves seamlessly into Linear Algebra & Polynomials (bedrocks of most CAS). Although meant to be concise, he proves, or sketches a proof of the important results. Finally, the meat of the book, C.A.N.T. One important problem is finding the "class number" (has to do with unique factorization, which we are all accustomed to in Z). A detailed description of the continued fraction algorithm (for finding the fundamental unit), and others made it very enlightening. He then deals with primality testing and factoring, two very important problems, the latter because of RSA. First, a description of the algorithm, then the theory behind it. He covered everything, from Trial Division (Dark Ages) to Pollard Rho to NFS (cutting-edge). Also included are some useful tables.

Of course, CAS information from 1993, won't be that helpful (look in his newest, Advanced Topics in C.A.N.T.).

Excellent. Also try Knuth's "Semi-numerical Algorithms" for a more computer oriented approach.