Best Computer Performance Optimization

Having sold more than 2 million copies over its lifetime, How Computers Work is the definitive illustrated guide to the world of PCs and technology. Whether your interest is in business, gaming, digital photography, entertainment, communications, or security, you’ll learn how computing is evolving the way you live. Only the accomplished and award-winning team of writer Ron White and artist Tim Downs has the unique ability to meld descriptive text with one-of-a-kind visuals to fully explain how the electronic gear we depend on every day is made possible. Ron White has been writing How Computers Work for 20 years, during which time he’s also been executive editor at PC Computing magazine, BYTE.com, and groovyPost.com.

The Art of Computer Systems Performance Analysis "At last, a welcome and needed text for computer professionals who require practical, ready-to-apply techniques for performance analysis. -Dr. Leonard Kleinrock University of California, Los Angeles "An entirely refreshing text which has just the right mixture of theory and real world practice. The Art of Computer Systems Performance Analysis is an essential tool for performance analysts, designers, purchasers, and users of computer systems.

Having sold more than 2 million copies over its lifetime, How Computers Work is the definitive illustrated guide to the world of PCs and technology. Whether your interest is in business, gaming, digital photography, entertainment, communications, or security, you’ll learn how computing is evolving the way you live. Only the accomplished and award-winning team of writer Ron White and artist Tim Downs has the unique ability to meld descriptive text with one-of-a-kind visuals to fully explain how the electronic gear we depend on every day is made possible. How Computers Work was named best nonfiction computer book, and his writing has been honored by the Maggie Awards, the Robert F. Kennedy Journalism Awards, and The National Endowment for the Humanities.

In How to Create a Mind , Kurzweil presents a provocative exploration of the most important project in human-machine civilization—reverse engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines. “Kurzweil's vision of our super-enhanced future is completely sane and calmly reasoned, and his book should nicely smooth the path for the earth's robot overlords, who, it turns out, will be us.” —The New York Times “Kurzweil writes boldly and with a showman’s flair, expertly guiding the lay reader into deep thickets of neuroscience.” —Kate Tuttle, Boston Globe “This book is a breath of fresh air . His best so far!” —Marvin Minsky, MIT Toshiba Professor of Media Arts and Sciences; cofounder of the MIT Artificial Intelligence Lab; widely regarded as “the father of artificial intelligence” “If you ever wondered about how your mind works, read this book. This is an eloquent and thought-provoking work.” —Dean Kamen, physicist; inventor of the first wearable insulin pump, the HomeChoice dialysis machine, and the IBOT mobility system; founder of FIRST; recipient of the National Medal of Technology “One of the eminent AI pioneers, Ray Kurzweil, has created a new book to explain the true nature of intelligence, both biological and nonbiological. He provides a credible road map for achieving the goal of super-human intelligence, which will be necessary to solve the grand challenges of humanity.” —Raj Reddy, founding director, Robotics Institute, Carnegie Mellon University; recipient of the Turing Award from the Association for Computing Machinery “Ray Kurzweil pioneered artificial intelligence systems that could read print in any type style, synthesize speech and music, and understand speech. Just as Chanute’s Progress in Flying Machines ushered in the era of aviation over a century ago, this book is the harbinger of the coming revolution in artificial intelligence that will fulfill Kurzweil's own prophecies about it.” —Dileep George, AI scientist; pioneer of hierarchical models of the neocortex; cofounder of Numenta and Vicarious Systems.

In its Fourth Edition, Starting Out with Programming Logic and Design is a language-independent introductory programming book, ideal for a precursor programming course or the first unit of an introductory programming course. He is a highly acclaimed instructor who was previously selected as the North Carolina Community College “Teacher of the Year” and has received the Teaching Excellence award from the National Institute for Staff and Organizational Development. series includes introductory books covering Programming Logic and Design, C++, Java, Microsoft® Visual Basic, C#®, Python, and Alice, all published by Pearson.

What is RoboHelp? A frequent speaker at conferences and trade shows, Kevin was recognized by Adobe Systems, Inc. as one of their Top Five Most Highly Rated Adobe Certified Instructors, Worldwide.

--Details and deconstructs ITSM process components, models, and deliverables. --Includes strategies for gathering and analyzing process requirements to aid in analyzing and improving processes. --Shows how to engage process stakeholders and incorporate ITSM best practices into your organization. --Contains a methodology for developing meaningful metrics for your organization and ways to convert data into usable, actionable information. --WAV offers downloadable templates, plans, and checklists such as a sample process definition document, document control sheet, high-level implementation plan, key performance indicator checklist, and communication and training plans -- available from the Web Added Value Download Resource Center at jrosspub.com. The ITSM Process Design Guide: Developing, Rengineering and Improving IT Service Management closes the knowledge gap by providing detailed guidance on assessing, designing, measuring, and integrating ITSM processes.

A reorganized and comprehensive major revision of a classic book, this edition provides a bridge between introductory digital communications and more advanced treatment of information theory. In 1970 the first author published a book entitled An Introduction to Error-Correcting Codes, which presented the fundamentals of the previous two decades of work covering both block and convolutional codes. Other major additions included a comprehensive treatment of the error-detecting capabilities of block codes and an emphasis on soft decoding methods for convolutional codes. Three of these new developments stand out in particular: the application of binary convolutional and block codes to expanded (nonbinary) modulation alphabets, the development of practical soft decoding methods for block codes, and the discovery of soft-input, soft-output iterative decoding techniques for block and convolutional codes. A total of seven new chapters covering these topics have been added to this edition: two chapters on trellis- and block-coded modulation techniques, three chapters on soft decoding methods for block codes, and two chapters on turbo and low-density parity-check codes and iterative decoding. Chapters 3 through 10 cover in detail the fundamentals of block codes. Chapter 8 provides detailed coverage of majority-logic decodable codes, including the important classes of Euclidean and projective geometry codes. Chapter 9 develops the theory of the trellis structure of block codes, laying the groundwork for the introduction of trellis-based soft decoding algorithms in Chapter 14. Chapter 10, written by Professor Marc Fossorier, presents comprehensive coverage of reliability-based soft decoding methods for block codes and includes an introduction to iterative decoding techniques. Convolutional codes are introduced in Chapter 11, with the encoder state diagram serving as the basis for studying code structure and distance properties. Chapter 12 covers optimum decoding methods for convolutional codes, with an emphasis on the (maximum likelihood) Viterbi decoding algorithm for both hard and soft demodulator decisions. Chapter 13 covers suboptimum decoding methods for convolutional codes, with an emphasis on sequential decoding, using both the ZJ (stack) and Fano algorithms, and majority-logic decoding. Chapter 14 extends the soft decoding methods introduced for convolutional codes in Chapter 12 to block codes. This completely new chapter makes extensive use of the block code trellis structures introduced in Chapter 9. Chapter 15 discusses the important concepts of code concatenation, multistage decoding, and code decomposition. Chapter 16 introduces the area of parallel concatenation, or turbo coding, and its related iterative decoding techniques based on the BCJR algorithm presented in Chapter 12. Both block (Chapter 20) and convolutional (Chapter 21) burst-error-correcting codes are included. As a text the book can be used as the basis for a two-semester sequence in coding theory, with Chapters 1-10 on the fundamentals of block codes covered in one semester and the remaining chapters on convolutional codes and advanced block code topics in a second semester. Another possibility is to cover Chapters 1-8 and 11-13, which include the fundamentals of both block and convolutional codes, in one semester, followed by a second semester devoted to advanced topics. A course on block codes comprise Chapters 1-7 plus selected topics from Chapters 8-10, 14-15, 17, 19-20, and 22, whereas Chapters 1, 11-13, 16, 18, and 21 provide a thorough coverage of convolutional codes.

This fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms is the leading textbook on algorithms today and is widely used in colleges and universities worldwide. The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. Robert Sedgewick has been a Professor of Computer Science at Princeton University since 1985, where he was the founding Chairman of the Department of Computer Science.

And as such, I know what it's like to be asked to whip up brilliant algorithms on the spot and then write flawless code on a whiteboard. Learn how to uncover the hints and hidden details in a question, discover how to break down a problem into manageable chunks, develop techniques to unstick yourself when stuck, learn (or re-learn) core computer science concepts, and practice on 189 interview questions and solutions. Extensive coverage of essential topics, such as big O time, data structures, and core algorithms. At Google, she interviewed hundreds of software engineers and evaluated thousands of hiring packets on the hiring committee.

A reorganized and comprehensive major revision of a classic book, this edition provides a bridge between introductory digital communications and more advanced treatment of information theory. In 1970 the first author published a book entitled An Introduction to Error-Correcting Codes, which presented the fundamentals of the previous two decades of work covering both block and convolutional codes. Other major additions included a comprehensive treatment of the error-detecting capabilities of block codes and an emphasis on soft decoding methods for convolutional codes. Three of these new developments stand out in particular: the application of binary convolutional and block codes to expanded (nonbinary) modulation alphabets, the development of practical soft decoding methods for block codes, and the discovery of soft-input, soft-output iterative decoding techniques for block and convolutional codes. A total of seven new chapters covering these topics have been added to this edition: two chapters on trellis- and block-coded modulation techniques, three chapters on soft decoding methods for block codes, and two chapters on turbo and low-density parity-check codes and iterative decoding. Chapters 3 through 10 cover in detail the fundamentals of block codes. Chapter 8 provides detailed coverage of majority-logic decodable codes, including the important classes of Euclidean and projective geometry codes. Chapter 9 develops the theory of the trellis structure of block codes, laying the groundwork for the introduction of trellis-based soft decoding algorithms in Chapter 14. Chapter 10, written by Professor Marc Fossorier, presents comprehensive coverage of reliability-based soft decoding methods for block codes and includes an introduction to iterative decoding techniques. Convolutional codes are introduced in Chapter 11, with the encoder state diagram serving as the basis for studying code structure and distance properties. Chapter 12 covers optimum decoding methods for convolutional codes, with an emphasis on the (maximum likelihood) Viterbi decoding algorithm for both hard and soft demodulator decisions. Chapter 13 covers suboptimum decoding methods for convolutional codes, with an emphasis on sequential decoding, using both the ZJ (stack) and Fano algorithms, and majority-logic decoding. Chapter 14 extends the soft decoding methods introduced for convolutional codes in Chapter 12 to block codes. This completely new chapter makes extensive use of the block code trellis structures introduced in Chapter 9. Chapter 15 discusses the important concepts of code concatenation, multistage decoding, and code decomposition. Chapter 16 introduces the area of parallel concatenation, or turbo coding, and its related iterative decoding techniques based on the BCJR algorithm presented in Chapter 12. Both block (Chapter 20) and convolutional (Chapter 21) burst-error-correcting codes are included. As a text the book can be used as the basis for a two-semester sequence in coding theory, with Chapters 1-10 on the fundamentals of block codes covered in one semester and the remaining chapters on convolutional codes and advanced block code topics in a second semester. Another possibility is to cover Chapters 1-8 and 11-13, which include the fundamentals of both block and convolutional codes, in one semester, followed by a second semester devoted to advanced topics. A course on block codes comprise Chapters 1-7 plus selected topics from Chapters 8-10, 14-15, 17, 19-20, and 22, whereas Chapters 1, 11-13, 16, 18, and 21 provide a thorough coverage of convolutional codes.

Martin has teamed up with his colleagues from Object Mentor to distill their best agile practice of cleaning code “on the fly” into a book that will instill within you the values of a software craftsman and make you a better programmer—but only if you work at it. Clean Code is divided into three parts. How to tell the difference between good and bad code How to write good code and how to transform bad code into good code How to create good names, good functions, good objects, and good classes How to format code for maximum readability How to implement complete error handling without obscuring code logic How to unit test and practice test-driven development. Robert C. “Uncle Bob” Martin has been a software professional since 1970 and an international software consultant since 1990.

Using the Smarter Way to Learn method, you actually learn HTML/CSS, you don’t just read about it. Read the reviews that call The Smarter Way of learning fun, involving, frustration-free, and confidence-building. Then, if you want to go beyond reading about HTML & CSS and actually learn the skills, do it the smarter way.

These texts cover the design of object-oriented software and examine how to investigate requirements, create solutions and then translate designs into code, showing developers how to make practical use of the most significant recent developments. Design Patterns is a modern classic in the literature of object-oriented development, offering timeless and elegant solutions to common problems in software design.

These texts cover the design of object-oriented software and examine how to investigate requirements, create solutions and then translate designs into code, showing developers how to make practical use of the most significant recent developments. Design Patterns is a modern classic in the literature of object-oriented development, offering timeless and elegant solutions to common problems in software design.

Using a step-by-step case study to illustrate the concepts and topics in each chapter, Bruegge and Dutoit emphasize learning object-oriented software engineer through practical experience: readers can apply the techniques learned in class by implementing a real-world software project. This book is about conquering complex and changing software systems. The application domain (mountain expedition planning, air traffic control, financial systems, word processing) usually includes many concepts that software developers are not familiar with. The solution domain (user interface toolkits, wireless communication, middleware, database management systems, transaction processing systems, wearable computers, etc.). Consequently, the system and the development project are complex, involving many different components, tools, methods, and people. As quality control finds defects in the system and users request new features, developers modify the system and its associated work products, resulting in continuous change. This book reflects more than 10 years of building systems and of teaching software engineering project courses. Reacting to this state of affairs, the typical undergraduate curriculum now often includes a software engineering project course, organized as a single development project. We use examples from real systems and examine the interaction between state-of-the art techniques, such as UML (Unified Modeling Language), Java-based technologies, design patterns, design rationale, configuration management, and quality control. Understanding complexity can only be gained by working with a complex system; that is, a system that no single student can completely understand. When trying to understand and model the application domain, developers interact regularly with others, including users and clients, some of whom know little about software development. Even if developers build software for developers only, they would still need to communicate among themselves. Instead, we focus on a limited set of techniques and explain their application in a reasonably complex environment, such as a multiteam development project that includes 20-60 participants. In Chapter 1, Introduction to Software Engineering, we describe the difference between programming and software engineering, the current challenges in our discipline, and basic definitions of concepts we use throughout the book. In Chapter 2, Modeling with UML, we describe the basic elements of a modeling language, UML (Unified Modeling Language), used in object-oriented techniques. Subsequent chapters teach the reader how to build UML diagrams to model various aspects of the system. We use UML throughout the book to model a variety of artifacts, from software systems to processes and work products. In Chapter 3, Project Communication, we discuss the single most critical activity that developers perform. In Part II, Dealing with Complexity, we focus on methods and technologies that enable developers to specify, design, and implement complex systems. In Chapter 4, Requirements Elicitation, and Chapter 5, Analysis, we describe the definition of the system from the users' point of view. In Chapter 6, System Design, we describe the definition of the system from the developers' point of view. We refine the requirements and system models and specify precisely the classes that constitute the system and define the boundary of existing class libraries and frameworks. The models we develop during requirements elicitation, analysis, and system design help us deal with complexity, by providing us with different perspectives on what the system should be doing and how it should do it. In Chapter 9, Testing, we describe the validation of system behavior against the system models. Testing detects faults in the system, including those introduced during changes to the system or its requirements. In Chapter 10, Software Configuration Management, we describe techniques and tools for modeling the project history. Change management ensures that modifications to the system are consistent with project goals. In Chapter 11, Project Management, we describe techniques necessary for initiating a software development project, tracking its progress, and dealing with risks and unplanned events. In Chapter 12, Software Life Cycle, we describe software life cycles, such as Boehm's Spiral Model and the Unified Software Development Process, which provide an abstract model of development activities. We expect that students have the necessary problem-solving skills to attack technical problems, but we do not expect that they have been exposed to complex or changing situations typical of system development. An instructor may consider teaching early in the course introductory project management concepts from Chapter 11, Project Management, such that students become familiar with planning and status reporting. A management course focusing on managerial aspects such as communication, risk management, rationale, maturity models, and UML could use the chapter sequence 1, 2, 11, 3, 4, 8, 10, 12.