Minggu, 28 Februari 2010

[Y403.Ebook] Ebook Download UML Bible, by Tom Pender

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UML Bible, by Tom Pender

* Comprehensive coverage of all aspects of UML (Unified Modeling Language), including use, diagramming notation, the object constraint language, and profiles
* UML is the industry standard specification for modeling, visualizing, and documenting software projects
* Includes up-to-date coverage of both UML 1.4 and the new 2.0 UML specifications
* Thoroughly covers executable UML and testing UML diagrams, making coding more efficient
* Companion Web site provides additional code samples and updates

  • Sales Rank: #1474948 in Books
  • Brand: Brand: Wiley
  • Published on: 2003-09-26
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.20" h x 2.10" w x 7.50" l, 3.01 pounds
  • Binding: Paperback
  • 984 pages
Features
  • Used Book in Good Condition

From the Back Cover
If UML can do it, you can do it too...

Today’s economy demands top quality software development in record time and with maximum efficiency. UML arms you to meet that challenge, and the UML Bible supplies the most comprehensive UML education you can get. One volume covers everything from understanding and using UML and diagramming notation to the object constraint language (OCL) and profiles, in both 1.4 and 2.0 UML specifications. It’s the one resource you can rely on to virtually guarantee your success.

Inside, you’ll find complete coverage of UML

  • Learn to model object structure, interactions, behavior, and architecture using UML
  • Explore diagram structure and usage
  • Understand how to utilize the overlapping features of the UML diagrams to facilitate the modeling process
  • Learn to exploit the features of the UML diagrams to test them for consistency and accuracy
  • Learn to assess modeling tools to choose the one that suits your needs
  • Comprehend how the statechart diagram is used to model changes in an object over its lifetime
  • Apply object constraint language (OCL) and work with Action Semantics to specify behaviors that ultimately will be implemented in code
  • Understand the XML Model Interchange (XMI�) standard that helps enable model sharing between modeling tools and other XMI-compatible applications
  • Customize UML to meet the needs of specific industries or application types

About the Author
Tom Pender has been working in software development for over 22 years. Most recently he has author six courses on the UML which he has taught throughout the U.S. and 12 other countries. He has also spent the last four years teaching and consulting with companies who are transitioning to object-oriented technologies. Prior to that, his software development roles included everything from programmer to manager, teacher, writer, business systems analyst, and consultant. His work has spanned wholesale and retail distribution, investing, insurance, accounting, international shipping, embedded phone applications, materials management, and coal mining.

Most helpful customer reviews

0 of 0 people found the following review helpful.
One Star
By Gordon Matheson
Wouldn't want to document a design without this book.

5 of 5 people found the following review helpful.
Excellent book for medium to advanced UML users
By Amazon Customer
The book is laid out very well, starting with a review of UML and provides thorough and detailed descriptions of all the diagrams and notations. I'm using this nearly exclusively to help me model projects, and is on my desk instead of on my bookshelf.

The author clearly understands UML and takes the reader effectively through the distinctions between the many notations.

Pluses
- Excellent description on the differences between UML 1.4 and 2.0, including completely different chapters where necessary
- Detailed descriptions of all the notations including less often used pieces
- Explicit definitions of key terms that limit confusion created from the "common understanding" of the definitions
- Excellent example that runs through the entire book, with appropriate departures to clarify points.
- Valuable introduction to the Object Constraint Language (OCL) and action semantics
- Most information that belongs in the appendix / late chapters is there (see below)

A few dings -

First, I would have to agree with Mr. Duff's comments on the target audience - I'm fairly experienced with Object Oriented programming and with design work, but when I tried to read this, I started getting confused and very sleepy. I started out with UML for Dummies and this made life much easier.

Second, the author included an early chapter and 50 pages throughout the book to the architecture and formal definition of UML. Frankly, I'm not sure who is really interested in the definition of the UML 1.4 four layer architecture model and the UML 2.0 superstructure library, but to me the bigger sin is to put it in chapter 2 instead of an appendix / later chapter. I didn't gain anything except a headache by reading about it earlier in the book.

Third, although he is very clear about it through the book, the version that I have came out before the final specification. This may cause some things to be different from his version to the final specification. However, he details those specifically, gives the likely outcomes, and the detailed areas are in the hinterlands of UML.

20 of 21 people found the following review helpful.
About as comprehensive a book as you can find on UML...
By Thomas Duff
If you are at all involved with the use of UML in your programming or analysis activities, you'll most likely be interested in seeing the UML Bible by Tom Pender (Wiley). Like all 'Bible' titles from Wiley, this book covers a wide range of topics that should give you most any answer you need to find.
The chapter breakout is in seven parts:
Part 1 - An Introduction to UML - What Is UML?; UML Architecture; UML Diagrams and Extension Mechanisms; Object-Oriented Concepts
Part 2 - Modeling Object Structure - Capturing Rules about Objects in a Class Diagram; How to Capture Rules about Object Relationships; Testing With Objects
Part 3 - Modeling Object Interactions - Modeling Interactions in UML 1.4; Modeling Interactions in UML 2.0; Modeling an Object's Lifecycle in UML 1.4; Modeling an Object's Lifecycle in UML 2.0
Part 4 - Modeling Object Behavior - Modeling the Use of a System with the Use Case Diagram; Modeling Behavior Using an Activity Diagram
Part 5 - Modeling the Application Architecture - Using Packages; Modeling Software Using the Component Diagram; Using Deployment Diagrams in UML 1.4; Using Deployment Diagrams in UML 2.0
Part 6 - Bringing Rigor to the Model - Applying Constraints to the UML Diagrams; Action Semantics
Part 7 - Automating the UML Modeling Process - Using a Modeling Tool; Customizing UML Using Profiles; XML Metadata Interchange
Appendices - UML 1.4 Notation Guide; UML 2.0 Notation Guide; Standard Elements; Glossary; Index
Now, I'm not a UML expert by any stretch of the imagination. But based on what I have read and studied to date, this book covers everything. Taking the Use Case chapter as an example, I can see that there is an abundance of technical detail and diagramming to explain the topic completely. Couple this chapter with the notation guide in the back, and you have a reference guide that is hard to beat. At the time this book was written, UML 2.0 wasn't yet released. But the author takes the specs that should be part of the final release and explains how those features are different than UML 1.4. As a result, you shouldn't outgrow this book anytime soon.
The only quibble I have with the book is the audience that the author says he is targeting. Readers new to object-oriented analysis are expected to be able to get an in-depth understanding of UML and be able to become a productive member of a team by reading this book. In my opinion, that may be a bit of a reach. If I had no UML experience, I'd find this book very daunting in both the size and complexity of the material. My recommendation would be to find an entry level UML book, and work through it before tackling this book. With the UML fundamentals fresh in your mind, you'll be able to come at this book from a much better position and benefit much more quickly.
Overall, a good book to have around...

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Sabtu, 13 Februari 2010

[N366.Ebook] Ebook Download MTI Broadway Junior Collection: Legally Blonde The Musical JR. Actor's Script, by Heather Hach

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MTI Broadway Junior Collection: Legally Blonde The Musical JR. Actor's Script, by Heather Hach

MTI Broadway Junior Collection: Legally Blonde The Musical JR. Actor's Script

  • Sales Rank: #6442898 in Books
  • Published on: 2014
  • Binding: Paperback
  • 139 pages

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Senin, 01 Februari 2010

[W361.Ebook] PDF Download R High Performance Programming, by Aloysius Lim, William Tjhi

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R High Performance Programming, by Aloysius Lim, William Tjhi

Overcome performance difficulties in R with a range of exciting techniques and solutions

About This Book
  • Benchmark and profile R programs to solve performance bottlenecks
  • Combine the ease of use and flexibility of R with the power of big data tools
  • Filled with practical techniques and useful code examples to process large data sets more efficiently
Who This Book Is For

This book is for programmers and developers who want to improve the performance of their R programs by making them run faster with large data sets or who are trying to solve a pesky performance problem.

What You Will Learn
  • Benchmark and profile R programs to solve performance bottlenecks
  • Understand how CPU, memory, and disk input/output constraints can limit the performance of R programs
  • Optimize R code to run faster and use less memory
  • Use compiled code in R and other languages such as C to speed up computations
  • Harness the power of GPUs for computational speed
  • Process data sets that are larger than memory using disk-based memory and chunking
  • Tap into the capacity of multiple CPUs using parallel computing
  • Leverage the power of advanced database systems and Big Data tools from within R
In Detail

With the increasing use of information in all areas of business and science, R provides an easy and powerful way to analyze and process the vast amounts of data involved. It is one of the most popular tools today for faster data exploration, statistical analysis, and statistical modeling and can generate useful insights and discoveries from large amounts of data.

Through this practical and varied guide, you will become equipped to solve a range of performance problems in R programming. You will learn how to profile and benchmark R programs, identify bottlenecks, assess and identify performance limitations from the CPU, identify memory or disk input/output constraints, and optimize the computational speed of your R programs using great tricks, such as vectorizing computations. You will then move on to more advanced techniques, such as compiling code and tapping into the computing power of GPUs, optimizing memory consumption, and handling larger-than-memory data sets using disk-based memory and chunking.

  • Sales Rank: #889830 in Books
  • Published on: 2015-01-30
  • Released on: 2015-01-29
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.25" h x .40" w x 7.50" l, .0 pounds
  • Binding: Paperback
  • 180 pages

About the Author

Aloysius Lim

Aloysius Lim has a knack for translating complex data and models into easy-to-understand insights. As cofounder of About People, a data science and design consultancy, he loves solving problems and helping others to find practical solutions to business challenges using data. His breadth of experience―7 years in the government, education, and retail industries―equips him with unique perspectives to find creative solutions.



William Tjhi

William Tjhi is a data scientist with years of experience working in academia, government, and industry. He began his data science journey as a PhD candidate researching new algorithms to improve the robustness of high-dimensional data clustering. Upon receiving his doctorate, he moved from basic to applied research, solving problems among others in molecular biology and epidemiology using machine learning. He published some of his research in peer-reviewed journals and conferences. With the rise of Big Data, William left academia for industry, where he started practicing data science in both business and public sector settings. William is passionate about R and has been using it as his primary analysis tool since his research days. He was once part of Revolution Analytics, and there he contributed to make R more suitable for Big Data.

Most helpful customer reviews

3 of 3 people found the following review helpful.
Practical examples and detailed explanations
By Christian S.
I enjoyed reading this book and following the code examples.

The first chapter does a good job explaining the internals of R and analyzing its performance characteristics.
It does not dissect the complete language (for that I would recommend you Advanced R from Hadley) but the important parts which impact performance.

The second chapter shows you several tools and techniques to measure and profile your code.

The simple tweaks chapters are quite illustrative and have very interesting examples.
For example just switching the BLAS version included with R with the one that comes with Mac OS X shows great performance improvement.
It explains and gives you advice on how to choose the right data structures. Don't make everything a data.frame!

One of the most interesting chapters for me was Processing Large Datasets with Limited RAM.
With the size of current available datasets, the amount of RAM available becomes an issue.
The author discusses several techniques and libraries to deal with this issue.

Another well explained section is Parallel Computing. It has very nice examples as well.
This topic is really important to fully utilize the CPUs we have paid for in our PCs.

I also liked the GPU chapter, I was not aware of the GPU support in R.
It is a very nice surprise and if you don't have a computer with GPUs you can try one of the Amazon AMIs the author suggests.
GPUs are the state-of-the-art in Deep Learning and it is great to see that R has libraries that support it.

The last chapter introduces the use of R and Hadoop to deal with large scale processing.
It gives you a nice step-by-step setup so you can try in Amazon.

In summary I recommend this book, although the content is broad, it gives you enough for you to start going deeper in any of these topics.

1 of 1 people found the following review helpful.
Aloysius and William cover the code execution benchmarking techniques at the beginning very well and then make you embark on won
By A. Zubarev
R High Performance Programming is probably a unique book in terms of the material covered, I just have not see yet to date a book that is dedicated to increasing the computational capacity of the R language.

And I need to state frankly, since R has left the academic circles a long time ago and now is being used more and more in applications involving the Big Data calibre of projects a developer or an R user needs to understand its limitations and perhaps even be able to shrug off some misconceptions that surface on and off about the R’s Big Data suitability.

This book will make you prepared to cope with those who encroach on R’s capability to process petabytes of data. Bedsides, since the authors have a very broad outlook on the technologies and succeeded to cover very difficult topics in simple terms this book actually is of an asset to any software developer, using any language on any platform

What do you need for this book: preferably a *NIX based 64 bit machine capable enough to run a Virtual Machine with an NVIDIA GPU. An Amazon EWS account. Eclipse R Add on (R Studio was cited as storing object state). A Windows user will be able to learn as much, but some of the libraries covered in the book (just a few) were not ported to Windows at the time of my reading.

Aloysius and William cover the code execution benchmarking techniques at the beginning very well and then make you embark on wonderful journey to exploring an array of CRAN packages, third party tools and frameworks, the book includes the use of Hadoop, PostgreSQL, MonetDB (vertical data store), Pivotal SciDB, and more so you will not be limited to a narrow subset of tools to use under your belt, it will be something like dirking from the firehose!

I read this book in one breath, it is was just that a fascinating journey. I now think I need to come back, and read several chapters of immense interest to me: code pre-compilation (just so easy to take advantage of), the FF, dplyr and BigMemory package (just take advantage of somebody giving you a hand). I will experiment with at least one database, perhaps MonetDB as being at fingertips reach.

If I had a small complaint that would be for the absence of the statistical visualizations code – I just would like to benchmark my own improvements.

All in all, it is a fantastic book, thank you Aloysius and William! A very timely release Packt!

My verdict, is it a superb reading!

2 of 2 people found the following review helpful.
Two good books trying to coexist in one body
By Daniel Lee
R High Performance Programming is a fun book if you're interested in optimizing computation speed in R, especially if you're working with large amounts of data. I found the code examples easy to follow and the author did a good job of showing and interpreting profiling results.

Although the book has some nice examples on how to improve performance in R, and it also did a pretty good job of explaining why R's implementation can lead to bottlenecks, I had the impression that it was in the middle of an identity crisis. There was a lot of discussion of general tips on how to optimize code - preallocating data structures, using types with small memory footprints, identifying speed bottlenecks to optimize effectively, principles of parallelization - the sections that covered these issues were fairly shallow. I would expect that most readers are already familiar with the general principles outlined in the book, so they weren't the most helpful tips I've found. This becomes increasingly clear when you look at the examples the author shows you - if you're able to use the packages he introduces for using R with a GPU or Hadoop, you're already familiar with the tricks he describes.

In my opinion, the book would have been a lot more useful, had the author decided either to write about optimizing code in dynamic languages in general and then going into more detail, or if he would have made a cookbook that goes into more depth on the packages he introduced. Your mileage may vary, but although the book was well written, I would have profited more from a cookbook or even just a short summary of available packages with kurt descriptions.

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