Showing posts with label algorithms. Show all posts
Showing posts with label algorithms. Show all posts

Algorithms: Design Techniques and Analys (Lecture Notes Series on Computing) Review

Algorithms: Design Techniques and Analys (Lecture Notes Series on Computing)
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Algorithms: Design Techniques and Analys (Lecture Notes Series on Computing) ReviewThe book represents a well written, consistent and easy to follow view on the area of algorithm analysis. It gives an excellent overview of various mathematical and computer science areas, including but not limited to combinatorial geometry, NP-problems, complexity theory, graph theory, algorithm analysis, dynamic programming and even computational geometry.
Most of the chapters are intended for a senior level undergraduate and graduate student, but some (such as part 4 devoted to complexity problems) are more suitable for "mature" audience and require some preliminary knowledge in the area.
I found chapters on sorting, data structures, recursion and functional programming well written and structured, and examples to be practical as well as informative.
Sections on amortized analysis, randomized algorithms, approximation algorithms and iteration improvement deal with current directions in the algorithmic research and provide an excellent overview of the "state-of-the-art" in these areas. I also enjoyed reading through the section on greedy algorithms (shortest path and minimum spanning tree problems).
Section on computational complexity and analysis of the relationship between complexity classes seems to be a bit complicated, those who are interested in this area should probably do some preliminary reading.
The last section on computational geometry (my area of expertise) and applications of Voronoi diagrams could be extended, but even in the current state it givs a pretty good idea of what computational geometry is all about.
Overall, I give to this book a "5 star" review and recommend it for anyone who is seriously interested in learning exactly how algorithm design and analysis work. I thoroughly enjoyed reading this book and can only wish that author would write more books like that in the future!Algorithms: Design Techniques and Analys (Lecture Notes Series on Computing) Overview

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Data Structures and Program Design In C (2nd Edition) Review

Data Structures and Program Design In C (2nd Edition)
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Data Structures and Program Design In C (2nd Edition) ReviewI just finished an online course on data structures at UMass, Lowell (secured an A grade without any problem) and this is the textbook used for this course. I agree with some of the comments made by the reviewers here - that typedef's are used beyond reason, code is presented in fragments. I must strongly disagree with the reviewers who said - the book is not worth the money (it's cheap if you buy a used one), it is a bad book, useful only as a paper weight. The strong plus point for this book is that it presents theory well - there are many figures using which it is easy to understand complicated stuff. The other plus point is that it also analyzes the performance of algorithms and I felt the book does a great job of explaining this part in clear terms. The main drawback is that the code is fragmented and spread out, which is certainly frustating. Also, in order to get the code to work on a compiler (I used Microsoft VC++ version 6), you will need to "fill in the gaps" as most code examples (I tried 90% of the examples in the text on MVC++ compiler) are by no means complete but this was not difficult. You can download the code from the publisher's website and the code is actually not organized into different files (sorted by chapter and example) but it comes in a few files where examples from different chapters are mixed. You will have to search and find the part you need. I do agree usage of dummy functions creates confusion. This book has a rocky start with the life game example, which was not very easy to follow with the explanation provided. While I was frustated with the first two chapters, the rest of the chapters are presented well. To the reviewer who said that the code has bugs (which certainly isn't true), my guess that the gaps are not properly filled. I patiently tested most of the code on the computer (after filling in the gaps of course!) and find absolutely no problems with it. This however took lot of time since significant effort is needed from the student to fill the missing code to make it work. I have supplied working code to my fellow students who were facing difficulties in getting the code to run. In a couple of places in the text, the author surprised me with C syntax I did not know was legal (I consider myself intermediate programmer).
I suspect the reason why many readers have problems with this book is two-fold: 1.The code is not available in a format that can be tested on the compiler. Having read a lot of CS books which supply with readily usable code, this book gets annoying. I was wondering why the authors did not give downloadable working code for all examples in the text (which is a definite minus point) 2. The reader will have to go back and forth between the chapters as some functions developed in former chapters are used in later chapters. This does get irritating. I have read books that do this to a ridiculous level but this book stays with in tolerable bounds.
I will not rate this book as the best one on the subject out there but it is definitely good enough to learn data structures. I have used another book as a supplement: Data Structures & Algorithms in Java (Mitchell Waite Signature Series) (Hardcover) By Mitchell Waite, Robert Lafore ISBN: 1571690956. This book has lot of applets that show step by step how algorithms work. I am a visual learner and this helped tremendously. However, I felt that Waite Series book did not present the theory as thoroughly as Robert Kruse's text.
In summary, I consider this book as "decent". I was very much concerned when I first purchased this text because of so many bad reviews. As it turns out, those that can understand C and are willing to sit in front of the computer to make the code samples in this book work need not have any fear. As I said earlier, the theory is presented well, and all it needs is patience and diligence from the student to go through the code examples on a compiler. I believe that I now have a good understanding of the subject and I can move on books that deal with it at more depth. There are a plethora books on this topic out there and there may be better books than the ones mentioned in this review.Data Structures and Program Design In C (2nd Edition) Overview Progressing from the concrete to the abstract —and using numerous, substantial case studies and sample programs —this book explores structured problem solving, data abstraction,software engineering principles, and the comparative analysis ofalgorithms as fundamental tools of program design. Emphasizes principles of top-down refinement, programdesign, review, and testing. Uses the C programming languagethroughout. Offers Internet access to the source codefor all the programs and program extracts printed in the book.

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The Practice of Programming Review

The Practice of Programming
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The Practice of Programming ReviewIn computing, the learning curve is doubly steep. Not only do we have to learn very complex operations, but we have to learn them at a pace unrivaled in any other field. Furthermore, the equipment improves at a rate that simply boggles the mind. In this frantic environment, we rarely have time to read our code twice, much less read a book about code. Therefore, when we do read, we must make every minute count. This is one book where your count of wasted minutes would be a very small one.
Some of the tips in this book are obvious in retrospect, yet ones that you probably would not think of. My favorite is the fact that due to the changes in processors, a double precision floating point arithmetic operation can be faster than the equivalent one for integers. In the "old" days, the gospel was that you must avoid floating point operations unless absolutely necessary, to avoid the degradation of performance.
Other tips, such as methods to assure you comment what is necessary, taking a few minutes to learn simple performance features, debugging and testing guidelines; portability issues and basic algorithm analysis should cause you to pause for a moment. Even in our hectic development environments, stopping and analyzing your code is a necessity.
It is difficult to conceive of someone who will not find a tip in here that will justify the cost of the book. Unless of course, you are one of the authors. I listed it as one of the top books of the year in my On Books column that appeared in the September, 1999 issue of _Journal of Object-Oriented Programming_.The Practice of Programming Overview

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Artificial Intelligence: A Modern Approach (2nd Edition) Review

Artificial Intelligence: A Modern Approach (2nd Edition)
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Artificial Intelligence: A Modern Approach (2nd Edition) ReviewI didn't think that the first edition of this book was as bad as some of the reviewers said, but the second edition is definitely a vast improvement. It's not just some obligatory 2nd edition that some authors release to say that they are staying actively published. The first edition was somewhat confusing in its explanations and the exercises were really blurry on what was being asked. All of that has now been resolved.
The book is a comprehensive and insightful introduction to artificial intelligence with an academic tone. It provides a unified view of the field organized around the rational decision making paradigm, which focuses on the selection of the "best" solution to a problem. The book's overall theme is that the purpose of AI is to solve problems via intelligent agents, and then goes about specifying the features such an agent or agents should have. Pseudocode is provided for all of the major AI algorithms. Being about the broadest book in terms of coverage of AI, you should therefore not expect it to be the deepest in coverage. However, each topic is covered to the extent that the reader should understand its essence. Sections one through six are absolutely wonderful, and comprise the "meat" of AI. Section seven is rather weak since it tries to cover both robotics and text processing in their own individual chapters, and entire books have a hard time covering this material. Section eight is different from the others, since it talks about the philosophy and future of AI.
Another plus for this book is that there is a great deal of extra material that deals with standard AI curriculum. For example, the chapters on logic not only include the typical introduction to propositional and first order logic together with the usual inference procedures, they also give many useful hints how to use first order logic to actually represent aspects of the real world such as measures, time, actions, mental objects, etc. These chapters also contain much information about how to implement efficient logical reasoners.
Finally, this second edition has an excellent website that can be found by going through the publisher's webpage for the book. This website contains four sample chapters, pseudocode, and actual code in Java, Python, and LISP.
I notice that Amazon shows the table of contents from the first edition, so I am showing what the actual table of contents is for the second edition for the purpose of completeness. Note that the book has been significantly reorganized.
I. ARTIFICIAL INTELLIGENCE.
1. Introduction.
2. Intelligent Agents.
II. PROBLEM-SOLVING.
3. Solving Problems by Searching.
4. Informed Search and Exploration.
5. Constraint Satisfaction Problems.
6. Adversarial Search.
III. KNOWLEDGE AND REASONING.
7. Logical Agents.
8. First-Order Logic.
9. Inference in First-Order Logic.
10. Knowledge Representation.
IV. PLANNING.
11. Planning.
12. Planning and Acting in the Real World.
V. UNCERTAIN KNOWLEDGE AND REASONING.
13. Uncertainty.
14. Probabilistic Reasoning Systems.
15. Probabilistic Reasoning Over Time.
16. Making Simple Decisions.
17. Making Complex Decisions.
VI. LEARNING.
18. Learning from Observations.
19. Knowledge in Learning.
20. Statistical Learning Methods.
21. Reinforcement Learning.
VII. COMMUNICATING, PERCEIVING, AND ACTING.
22. Agents that Communicate.
23. Text Processing in the Large.
24. Perception.
25. Robotics.
VIII. CONCLUSIONS.
26. Philosophical Foundations.
27. AI: Present and Future.Artificial Intelligence: A Modern Approach (2nd Edition) Overview

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Algorithms, Data Structures, and Problem Solving With C++ Review

Algorithms, Data Structures, and Problem Solving With C++
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Algorithms, Data Structures, and Problem Solving With C++ ReviewI just finished a semester at the University of Texas at Austin in which this book was the text book for an abstract data types class. The book is a good textbook, but not a good desk reference.
The book is obviously written with students in mind, using rhetorical questions, leaving vital areas unexplained as "exercises for the reader", etc. As an introductory text, in an introductory class, the book served its purpose, though the professor was required to explain some of the details that the book lacked. The code that is included in the book is all written in pseudo-code, most of it does not compile without some tweaking, and when a student is trying to grasp a diffucult concept in graph theory, the last thing that student wants is to have to trace through the program, line-by-line, to catch some error that is irrelevant to the larger problem, such as semicolons that have been left out, unmatched parenthesis, variable names that are not allowed by most of the commercial compilers.
The book does have a good learning curve, however, and makes for good reading when first approaching a new computer science concept; however, when having to program a particularly hard section of a certain data structure, wading through pages of diatribe against older methods is not what is needed at that time.
For instance, after spending a large portion of an entire chapter on AVL trees, Weiss proceeds to give example code (that doesn't compile on Borland 5.0, Visual C++, or GNU compilers without some tweaking), but leaves out a crucial method! When first learning about AVL trees, one of the lessons that was drilled into our heads was the diffuculty of AVL deletion... yet the book summed it up in *one* sentence: "As with most data structures, deletion is the hardest task; it is left as an exercise to the reader."
Argh.Algorithms, Data Structures, and Problem Solving With C++ OverviewExperienced author and teacher Mark Allen Weiss now brings his expertise to the CS2 course with Algorithms, Data Structures, and Problem Solving with C++, which introduces both data structures and algorithm design from the viewpoint of abstract thinking and problem solving. The author chooses C++ as the language of implementation, but the emphasis of the book itself remains on uniformly accepted CS2 topics such as pointers, data structures, algorithm analysis, and increasingly complex programming projects.Algorithms, Data Structures, and Problem Solving with C++ is the first CS2 textbook that clearly separates the interface and implementation of data structures. The interface and running time of data structures are presented first, and students have the opportunity to use the data structures in a host of practical examples before being introduced to the implementations. This unique approach enhances the ability of students to think abstractly.Features * Retains an emphasis on data structures and algorithm design while using C++ as the language of implementation. * Reinforces abstraction by discussing interface and implementations of data structures in different parts of the book.* Incorporates case studies such as expression evaluation, cross-reference generation, and shortest path calculations. * Provides a complete discussion of time complexity and Big-Oh notation early in the text. * Gives the instructor flexibility in choosing an appropriate balance between practice, theory, and level of C++ detail. Contains optional advanced material in Part V. * Covers classes, templates, and inheritance as fundamental concepts in sophisticated C++ programs. * Contains fully functional code that has been tested on g++2.6.2, Sun 3.0.1, and Borland 4.5 compilers. Code is integrated into the book and also available by ftp. * Includes end-of-chapter glossaries, summaries of common errors, and a variety of exercises. 0805316663B04062001

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The C++ Standard Library: A Tutorial and Reference Review

The C++ Standard Library: A Tutorial and Reference
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The C++ Standard Library: A Tutorial and Reference ReviewOn my second reading, I'm still finding more gems in this book. Up to now, it was almost impossible to find any comprehensive material on the standard library. All one could find was the odd article about some aspect of the library, or rather specialized books about STL. Nicolai has fixed that particular problem once and for all.
The book reminds of Richard Stevens's famous UNIX books. Incredibly complete, incredibly detailed, incredibly accurate, and a great tutorial and reference at the same time. And, best of all, it's just as accessible to someone who is not a real expert as it is for someone who's been using C++ for years.
This is one of the *very* few books that get a spot on my top shelf. A classic that I will come back to again and again.The C++ Standard Library: A Tutorial and Reference OverviewThe C++ Standard Library provides a set of common classes and interfaces that greatly extend the core C++ language. Josuttis' book not only provides comprehensive documentation of each library component, it also offers clearly written explanations of complex concepts, describes the practical programming details needed for effective use, and gives example after example of working code. This thoroughly up-to-date book reflects the newest elements of the C++ standard library incorporated into the full ANSI/ISO C++ language standard. In particular, the text focuses on the Standard Template Library (STL), examining containers, iterators, function objects, and STL algorithms.

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Introduction to Algorithms (MIT Electrical Engineering and Computer Science) Review

Introduction to Algorithms (MIT Electrical Engineering and Computer Science)
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Introduction to Algorithms (MIT Electrical Engineering and Computer Science) ReviewI was the instructor for a junior/senior course on Algorithms at the University of Southern California and I used this book as the textbook. Unfortunately, many of the students didn't like this book because they did not appreciate the mathematical flavor of the book. A course on Algorithms is useless without a sound background in discrete mathematics. Hence, this book assumes that you are reasonably strong in Discrete Mathematics.
I haven't seen a better textbook ! Here are some reasons:
1. The discrete mathematics foundations are present in the first few chapters of this book and so, you can quickly brush up on any discrete math background that you may require while using this book.
2. The style of writing is very light and at the same time, rigorous - almost as if you are in the middle of a lecture while reading the book.
3. The material is comprehensive and serves as an excellent reference for other courses and in your future career.
4. The exercises and problems provide a very good learning experience.
5. It's a good-looking book !Introduction to Algorithms (MIT Electrical Engineering and Computer Science) OverviewThe first edition won the award for Best 1990 Professional and Scholarly Book in Computer Science and Data Processing by the Association of American Publishers. This edition is no longer available. Please see the Second Edition of this title.

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Applied Cryptography: Protocols, Algorithms, and Source Code in C, Second Edition Review

Applied Cryptography: Protocols, Algorithms, and Source Code in C, Second Edition
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Applied Cryptography: Protocols, Algorithms, and Source Code in C, Second Edition ReviewBruce Schneier's APPLIED CRYPTOGRAPHY is an excellent book for anyone interested in cryptology from an amateur level to actually being involved in the development of new encryption mechanisms. Schneier's book begins with a simple discussion of what is cryptography, and then he proceeds through the history of various encryption algorithms and their functioning. The last portion of the book contains C code for several public-domain encryption algorithms.
A caveat: this is not a textbook of cryptography in the sense that it teaches everything necessary to understand the mathematical basis of the science. Schneier does not discuss number theory because he expects those who use the relevant chapters of the book will already have training in higher maths. Nonetheless, the book does contain a wealth of information even for the layman.
One helpful part of Schneier's book is his opinion of which encryption algorithms are already broken by the National Security Agency, thus letting the reader know which encryption programs to avoid. There will always be people who encrypt to 40-bit DES even though it is flimsy and nearly instantly breakable, but the readers of APPLIED CRYPTOGRAPHY can greatly improve the confidentiality of their messages and data with this book. Discussion of public-key web-of-trust is essential reading for anyone confused by how public-key signatures work.
APPLIED CRYPTOGRAPHY was published in 1995 and some parts are already out of date. It is ironic that he hardly mentions PGP, when PGP went on to become the most renowned military-strength encryption program available to the public, although it is being superseded by GnuPG. Another anachronism is Schneier's assurance that quantum computing is decades away. In the years since publication of APPLIED CRYPTOGRAPHY we have seen some strides in quantum computer, even the creation of a quantum computer that can factor the number 15. While this publicly known quantum computer is not at all anything to get excited about, it is certain that more powerful quantum computers are in development and classified by NSA. Because a quantum computer can break virtually any traditional cipher, hiding the message (steganography) is becoming more important than ever. In the era of Schneier's book steganography was unnecessary because ciphertext could withstand brute-force attacks, but with advances in computing power steganography is becoming vital to secure communications. It would be nice to see the book updated with this topic, because cryptography and steganography can no longer be regarded as two distinct fields.
All in all, in spite of its age, APPLIED CRYPTOGRAPHY is recommended to anyone interested in cryptography. It ranks among the essential books on the field, although an updated version is certainly hoped for.Applied Cryptography: Protocols, Algorithms, and Source Code in C, Second Edition Overview

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Data Structures and Algorithms in Java (2nd Edition) Review

Data Structures and Algorithms in Java (2nd Edition)
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Data Structures and Algorithms in Java (2nd Edition) ReviewThis is an excellent book on data structures and algorithms and would be a great addition to a student's text book. Fortunately Lafore does not dwell on the algorithm analysis as many data structures books do. This is a plus for me, as most texts on the subject get the reader bogged down in the analysis portion of the subject matter. Note: algorithm analysis is a very important subject I just don't believe it should be taught in parallel with data structures to the extent it is. Its easier for me and many others to first learn how to implement data structures and get a feel for their performance then move on to in-depth analysis.
In this book you'll learn the more important data structures without the heavy mathematics many algorithm and data structure books torture readers with. The book is written in very accessible language and the applets really help the inexperienced see the algorithms in action.
As I mentioned this book does not cover algorithm analysis in detail. A step up from this book would be one of Sedgewick's books which provides more detail on the analysis front and some really 'tight' implementations. A good book that focuses on Algorithm Analysis is Intro to Algorithms by Cormen. You better have your math skills up to snuff for the Cormen book however.Data Structures and Algorithms in Java (2nd Edition) OverviewData Structures and Algorithms in Java, Second Edition is designed to be easy to read and understand although the topic itself is complicated. Algorithms are the procedures that software programs use to manipulate data structures. Besides clear and simple example programs, the author includes a workshop as a small demonstration program executable on a Web browser. The programs demonstrate in graphical form what data structures look like and how they operate. In the second edition, the program is rewritten to improve operation and clarify the algorithms, the example programs are revised to work with the latest version of the Java JDK, and questions and exercises will be added at the end of each chapter making the book evenmore useful.Educational SupplementSuggested solutions to the programming projects found at the end of each chapter are made available to instructors at recognized educational institutions. This educational supplement can be found at www.prenhall.com, in the Instructor Resource Center.

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Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics) Review

Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics)
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Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics) ReviewFor those who wants to understand what programns like spss, statistica and minitab do. Its not trivial but for the midle level student its very usefull. All the examples are in fortram language what is bad for me... But in general Monahan writes in very clear way, special thing in this kind of book.Numerical Methods of Statistics (Cambridge Series in Statistical and Probabilistic Mathematics) OverviewThis book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis.For statisticians, it examines the nitty-gritty computational problems behind statistical methods. For mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book offers a basic background in numerical analysis that emphasizes issues important to statisticians.The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression.The author also treats the application of numerical tools; numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. The book concludes with an examination of sorting, FFT and the application of other "fast" algorithms to statistics.Each chapter contains exercises that range in difficulty as well as examples of the methods at work.Most of the examples are accompanied by demonstration code available from the author's home page.

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Data Structures and Algorithm Analysis in C (2nd Edition) Review

Data Structures and Algorithm Analysis in C (2nd Edition)
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Data Structures and Algorithm Analysis in C (2nd Edition) ReviewMany people on here have complained that this book goes way over the head of students not already familiar with some C++ and data structures. To these comments, I refer you to the product description (or editorial review, whichever) that specifically says this is an advanced text. I apologize to those whose professors ordered this book for intro data structures--I can understand why this book would go past the scope of that class. However, if you know any Object Oriented programming (Java or C++ preferably) and know some basic algorithms and structures (matrices, sorts, recursion, trees, queues, etc.) this book will take you far. I don't even mean that you must be proficient in these structures, just have some basic understanding of how they work. For example, you should know what a tree is (root, leaves, implemented with pointers and nodes) and book will tell you how to use trees (B-Trees, Binary trees, etc.). By the point you are using this book, hopefully you'll have taken the math and programming classes needed to comprehend this text. Otherwise, do not blame the text for being targeted to an advanced audience.Data Structures and Algorithm Analysis in C (2nd Edition) OverviewMark Allen Weiss' successful book provides a modern approach to algorithms and data structures using the C programming language. The book's conceptual presentation focuses on ADTs and the analysis of algorithms for efficiency, with a particular concentration on performance and running time. The second edition contains a new chapter that examines advanced data structures such as red black trees, top down splay trees, treaps, k-d trees, and pairing heaps among others. All code examples now conform to ANSI C and coverage of the formal proofs underpinning several key data structures has been strengthened.

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An Introduction to Bioinformatics Algorithms (Computational Molecular Biology) Review

An Introduction to Bioinformatics Algorithms (Computational Molecular Biology)
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An Introduction to Bioinformatics Algorithms (Computational Molecular Biology) ReviewIt's ironic that a new field like bioinformatics rarely offers any way for newcomers to feel welcome. Bioinformatics is maturing, and this book is that welcome.
It's written as a textbook for a Bioinformatics 101 course, the kind that has both computing and biology students in it. Historically, the two have lived in uneasy truce. The biologists thought that a 'database' was an enzyme that acted on 'datab'. The programmers would, in the authors' words, "spontaneously abort" at the chemistry and informality of biology. Maybe that's less true now, but the authors offer just enough computing basics for the biologists and just enough biology for the computer crowd to be able to discuss the same thing.
After that intro, the authors cover many of the classic problems in bioinformatics, including assembly, motif-finding, clustering, HMMs, dynamic programming, and even mass spec analysis. The style is very readable, and discusses both the biology and the computation of every topic presented. Many algorithms are built up in steps, showing how successive insights from both computation and biology can make existing techniques work better. Along the way, they offer biographical notes about the founders and luminaries of modern biological computation.
This is a great first book for anyone wanting to enter the field, from either a biology or a computer science background. Advanced students will bottom out quickly, and may lose patience with the informal and gently-paced discussion. Sorry, this book was never meant for them. It's a beginner's book, one that respects the intelligence and capability of its reader. It's broad, basic, and detailed enough that modest programming skill will yield working code. This book has my highest recommendation.
//wiredweirdAn Introduction to Bioinformatics Algorithms (Computational Molecular Biology) OverviewThis introductory text offers a clear exposition of the algorithmicprinciples driving advances in bioinformatics. Accessible to students in bothbiology and computer science, it strikes a unique balance between rigorousmathematics and practical techniques, emphasizing the ideas underlying algorithmsrather than offering a collection of apparently unrelated problems.The bookintroduces biological and algorithmic ideas together, linking issues in computerscience to biology and thus capturing the interest of students in both subjects. Itdemonstrates that relatively few design techniques can be used to solve a largenumber of practical problems in biology, and presents this material intuitively.AnIntroduction to Bioinformatics Algorithms is one of the first books onbioinformatics that can be used by students at an undergraduate level. It includes adual table of contents, organized by algorithmic idea and biological idea;discussions of biologically relevant problems, including a detailed problemformulation and one or more solutions for each; and brief biographical sketches ofleading figures in the field. These interesting vignettes offer students a glimpseof the inspirations and motivations for real work in bioinformatics, making theconcepts presented in the text more concrete and the techniques moreapproachable.PowerPoint presentations, practical bioinformatics problems, samplecode, diagrams, demonstrations, and other materials can be found at the Author'swebsite.

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Approximation Algorithms for NP-Hard Problems Review

Approximation Algorithms for NP-Hard Problems
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Approximation Algorithms for NP-Hard Problems ReviewDeveloping approximation algorithms for NP hard problems is now a very active field in Mathematical Programming and Theoretical Computer Science. This book is actually a collection of survey articles written by some of the foremost experts in this field.
Many of these developments are due to Mathemtical programming (primal dual, semidefinite programming et al). The most exciting of these has been the Goemans and Williamson algorithm for MAX CUT and MAX SAT. A good account of these techniques appears in Chapters 4 and 11.
On the other hand a sequence of unexpected results in complexity culminated in a proof that many of these problems cannot have polynomial approximation algorithms unless P=NP. A good survey of "Hardness of Approximations" appears in Chapter 10, written by Sanjeev Arora and Carsten Lund both of whom were responsible for some original developments in this field.
I am going to purchase a copy of this book and can only strongly recommend it to everyone.Approximation Algorithms for NP-Hard Problems OverviewThis is the first book to fully address the study of approximation algorithms as a tool for coping with intractable problems. With chapters contributed by leading researchers in the field, this book introduces unifying techniques in the analysis of approximation algorithms.

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Data Structures with C++ Using STL (2nd Edition) Review

Data Structures with C++ Using STL (2nd Edition)
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Data Structures with C++ Using STL (2nd Edition) ReviewThe book itself is great and illustrates the core concepts well.
The code examples are grossly out of date (were talking 1990's) and completely ruins the beautiful text by adding confusing, poorly written code examples to reinforce good literature.
If you are buying this to learn data structures as a reference, great.
If you expect usable code examples this is not the book for you.
Highly Microsoft Visual Studio Centric. Not ANSI C++.
My note to the author's / publisher: You need to keep up with the times. This is technology and it moves quickly. Otherwise future-proof your code as much as possible.Data Structures with C++ Using STL (2nd Edition) Overview This book uses a modern object-oriented approach to data structures, unified around the notion of the Standard Template Library (STL) container classes. The book presents a systematic development of data structures supported by numerous examples and complete programs. The authors separate the applications of a data structure from its implementation. Includes an applied study of interesting and classical algorithms that illustrate the data structures using only simple mathematical concepts (Big-O notation is introduced intuitively); Many additional figures are integrated into the presentation; ADT (Abstract Data Type) for each data structure—immediately used to solve appropriate problems; Early and accessible introduction to templates and iterators; Use of modern C++ constructs in developing data structures and their applications provides enough language detail to sufficiently understand the constructs.

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Data Structures and Algorithms in C++ Review

Data Structures and Algorithms in C++
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Data Structures and Algorithms in C++ ReviewThis is one of the dozens of Data Structures and Algorithms books in the market and till now the worst I've ever seen. I have taken two DSA courses in my undergrad years, and now as a grad, I'm TAing that course.
The theoretical treatment of the book is superficial and too childish. Yet, there's too little practical value. They discuss the unnecessary linked list implementations of trees which is quite confusing for students. I am also amazed that they do not mention finding or removing an element in a BST. And, more importantly there's too little discussion of graphs.
I don't understand those professors trying to bog down students with useless details and complicated C++ codes. Rather, they should give the intuition and the theory behind the data structures and algorithms. Weiss' book is much better than this one. But, even that is obsessed with doing tricky things with C++.
Anyway, to sum up: This book is a garbage. Stay away unless it's required for the course you're taking in case you may need to do homeworks and such.Data Structures and Algorithms in C++ Overview* Provides a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation* Each data structure is presented using ADTs and their respective implementations* Helps provide an understanding of the wide spectrum of skills ranging from sound algorithm and data structure design to efficient implementation and coding of these designs in C++Wiley Higher Education

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Visualizing Data: Exploring and Explaining Data with the Processing Environment Review

Visualizing Data: Exploring and Explaining Data with the Processing Environment
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Visualizing Data: Exploring and Explaining Data with the Processing Environment ReviewThis book allowed me to quickly create some simple applications using the processing API. So, in that respect, the book was successful. However, the book falls short in three respects.
1) One would expect a book with the title "Visualizing Data" to be crammed with pictures showing many different data visualizations. However, this book has relatively few. Every colleague of mine who passed by my desk and picked up the book had the exact same reaction.
2) The processing language is touted as a means for people unfamiliar with programming to get up to speed with visualization. However, I would be very surprised if anyone with little programming experience would get much out of this book.
3) Don't expect to use this book as a reference for the processing language. It is basically just a collection of half explained examples. Consider for example the function smooth(). This function appears in almost every example but forget about trying to find an explanation of what the function does in the book.
The book is probably worth buying to get up to speed quickly but plan on spending a significant amount of time sifting through the processing.org website and other online resources before being able to get anything non-trivial done. And if you don't already know Java then don't expect to accomplish anything even modestly complex without a lot of outside help.
Visualizing Data: Exploring and Explaining Data with the Processing Environment Overview
Enormous quantities of data go unused or underused today, simply because people can't visualize the quantities and relationships in it. Using a downloadable programming environment developed by the author, Visualizing Data demonstrates methods for representing data accurately on the Web and elsewhere, complete with user interaction, animation, and more. How do the 3.1 billion A, C, G and T letters of the human genome compare to those of a chimp or a mouse? What do the paths that millions of visitors take through a web site look like? With Visualizing Data, you learn how to answer complex questions like these with thoroughly interactive displays. We're not talking about cookie-cutter charts and graphs. This book teaches you how to design entire interfaces around large, complex data sets with the help of a powerful new design and prototyping tool called "Processing". Used by many researchers and companies to convey specific data in a clear and understandable manner, the Processing beta is available free. With this tool and Visualizing Data as a guide, you'll learn basic visualization principles, how to choose the right kind of display for your purposes, and how to provide interactive features that will bring users to your site over and over. This book teaches you:

The seven stages of visualizing data -- acquire, parse, filter, mine, represent, refine, and interact
How all data problems begin with a question and end with a narrative construct that provides a clear answer without extraneous details
Several example projects with the code to make them work
Positive and negative points of each representation discussed. The focus is on customization so that each one best suits what you want to convey about your data set
The book does not provide ready-made "visualizations" that can be plugged into any data set. Instead, with chapters divided by types of data rather than types of display, you'll learn how each visualization conveys the unique properties of the data it represents -- why the data was collected, what's interesting about it, and what stories it can tell. Visualizing Data teaches you how to answer questions, not simply display information.

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

Software Engineering: (Update) (8th Edition)
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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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Data Structures Using C Review

Data Structures Using C
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Data Structures Using C ReviewIf you are interested in trees (Binary Search,Generic & Multiway ) & Graphs this book could be a very good reference. Common Data Structures are also dealt with very nicely.Data Structures Using C OverviewUsing the increasingly popular C language, this book teaches datastructures from their theoretical conception through to their concreterealizations. It emphasizes structured design and programmingtechniques, and contains numerous debugged programming samples. For CS2course in advanced programming or data structures in C.

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Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching, Third Edition Review

Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching, Third Edition
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Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching, Third Edition ReviewIf you're looking for an exhaustive, upto-date reference/textbook for
fundamental, searching and sorting algorithms, then this is one of
the very best available.
Sedgewick has split his popular book into two volumes, with Graph
algorithms being hifted to the second volume. Moreover, many advanced
topics like computational geometry, fft, number theoretic algorithms
etc, which were introduced in the previous edition, seem to be missing
now - so the breadth of coverage seems to have reduced, which is a pity.
However, the depth has increased instead - i doubt that even Knuth
covers more sorting algorithms ! In particular, there are several
recent algorithms and data structures which are treated in greater
detail here than by Knuth. Of course, Knuth analyses all the
algorithms he presents in rigorous and exhaustive detail, which
this book doesn't.
Moreover, the book has many new algorithms and presents the state of the
art in sorting and searching algorithms, giving it a distinct advantage
over the older books.
Sedgewick makes it very clear in the preface that the emphasis is on
the practical importance of the algorithms, so esoteric algorithms which
are important 'only in theory' may find no mention. Also the emphasis is
more on the design of algorithms than on their analysis.
The number of (exercise!!) problems has multiplied manifold in this edition
to become more than most competing textbooks. Problems are graded by
difficulty level to help you choose the ones relevant to your needs.
The exposition is clear and authoritative - Prof. Sedgewick is a leading
authority in the field of algorithms and a student of Donald Knuth.
He has a gift for making difficult concepts seem simple, and the great
illustrations in the book go a long way in explaining the behaviour of
the algorithms.
For the practising professional, this is an ideal reference, since it'll
help you select the best algorithm for your task without bogging you
down with heavy mathematics.
The reasearcher, on the other hand, may benefit by gaining unique insights
from a master of the area, while using other books for the detailed
analysis of algorithms, including prehaps Sedgewick's own book on the
analysis of algorithms(with Flajolet).
A caveat - the code may not be 'ready to run'. It's better not to rely
on this book to provide you with usable code - if that is what you want,
perhaps the books by Drozdek/Weiss/Heileman/Rowe might be better choices.
If you want C code rather than C++, then the C version of this book is
a good choice, since the code provided is of 'K & R' class and therefore
a delight to read.
Of course, if you're looking for a language independent coverage,
then 'Introduction to algorithms' by Cormen,Leiserson and Rivest is
possibly the best book which combines rigor with comprehensive coverage
of the most important algorithms. Look out for the newly released
second edition.
And if you want a more rigorous and equally exhaustive coverage of
sorting and searching, go for Knuth vol.3 - still the authoritative
reference, though it may require more hard work on the reader's part.
Otherwise, invest in this and you won't be disappointed.Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching, Third Edition OverviewRobert Sedgewick has thoroughly rewritten and substantially expanded and updated his popular work to provide current and comprehensive coverage of important algorithms and data structures. Christopher Van Wyk and Sedgewick have developed new C++ implementations that both express the methods in a concise and direct manner, and also provide programmers with the practical means to test them on real applications.Many new algorithms are presented, and the explanations of each algorithm are much more detailed than in previous editions. A new text design and detailed, innovative figures, with accompanying commentary, greatly enhance the presentation. The third edition retains the successful blend of theory and practice that has made Sedgewick's work an invaluable resource for more than 250,000 programmers!This particular book, Parts 1n4, represents the essential first half of Sedgewick's complete work. It provides extensive coverage of fundamental data structures and algorithms for sorting, searching, and related applications. Although the substance of the book applies to programming in any language, the implementations by Van Wyk and Sedgewick also exploit the natural match between C++ classes and ADT implementations.Highlights Expanded coverage of arrays, linked lists, strings, trees, and other basic data structures Greater emphasis on abstract data types (ADTs), modular programming, object-oriented programming, and C++ classes than in previous editions Over 100 algorithms for sorting, selection, priority queue ADT implementations, and symbol table ADT (searching) implementations New implementations of binomial queues, multiway radix sorting, randomized BSTs, splay trees, skip lists, multiway tries, B trees, extendible hashing, and much more Increased quantitative information about the algorithms, giving you a basis for comparing them Over 1000 new exercises to help you learn the properties of algorithms Whether you are learning the algorithms for the first time or wish to have up-to-date reference material that incorporates new programming styles with classic and new algorithms, you will find a wealth of useful information in this book.

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Programming Challenges Review

Programming Challenges
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Programming Challenges ReviewBy far, the hardest part of teaching programming classes is evaluating the programs. Unless you have the students do only simplistic programs, they are difficult to read and running the executables does not always give an accurate appraisal of what was done. One possible solution to this educational conundrum is to take advantage of the robot judge maintained at the book's companion web site.
The book contains many problems to be solved via a program that must accept inputs having a specific, albeit general format and then produce the appropriate output. The robot judge is capable of evaluating programs written in Pascal, C, C++ and Java and it will return one of eleven different results, all of which are two letter acronyms. If the program is not given a passing grade, then the message will not be of much benefit.
The problems are placed in several categories, including sorting, combinatorics, number theory, graph traversal, grid operations and geometry. I identified several that I can and most likely will use as assignments the next time I teach basic programming. While some problems require significant background information, in general it is not so great that it is beyond the bounds of what can be done in a basic computing class. The problems were originally created to prepare students for programming contests, so the level of difficulty is such that they could not be used until later in a beginning course. However, the book would be an excellent text for any advanced programming class where the students are split into teams. Each chapter begins with primer material for the problems given in that chapter and I included it in my best books of the year 2003 column for the online "Journal of Object Technology".Programming Challenges OverviewThe challenges of problems from international programming competitions are an effective way to improve your algorithmic and coding skills and understanding.This volume uses international programming competition-type problems to motivate the study of algorithms, programming, and other topics in computer science. The book includes more than 100 programming challenges, as well as the theory and key concepts necessary for approaching them. Problems are organized by topic, and supplemented by complete tutorial material. Readers gain a concrete understanding of both algorithmic techniques and advanced coding topics. Unique Features:* Offers a wealth of rich programming problems suitable for self-study -- all with on-line judging at www.programming-challenges.com* Presents practice training for all major programming contests -- ACM International Collegiate Programming Contest (ACM ICPC), International Olympiad in Informatics (IOI), and Topcoder Challenge* Serves as a convenient, web-based means of adding a programming component to any algorithms or software engineering course * Contains complete working code for fundamental data structures and graph, string, numerical and geometric algorithms* Provides a brief-yet-thorough treatment of key elements in number theory, geometry, dynamic programming, and graph algorithms * Supports all popular programming languages (C, C++, Pascal, Java)Steven S. Skiena is a member of the faculty of computer science at SUNY Stony Brook and is author of many widely used books, including The Algorithm Design Manual. He received the 2001 IEEE Computer Society Undergraduate Teaching Award. Miguel Revilla is a member of the faculty of computer science at the University of Valladolid, Spain. He is official website archivist of the ACM ICPC and creator/maintainer of the primary robot-judge, contest-hosting website.

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