Provides information on how computer systems operate, how compilers work, and writing source code.

It's a critical lesson that today's computer science students aren't always being taught: How to carefully choose their high-level language statements to produce efficient code. Write Great Code, Volume 2: Thinking Low-Level, Writing High-Level shows software engineers what too many college and university courses don't - how compilers translate high-level language statements and data structures into machine code. Armed with this knowledge, they will make informed choices concerning the use of those high-level structures and help the compiler produce far better machine code - all without having to give up the productivity and portability benefits of using a high-level language.

Understanding the Machine, the first volume in the landmark Write Great Code series by Randall Hyde, explains the underlying mechanics of how a computer works. This, the first volume in Randall Hyde's Write Great Code series, dives into machine organization without the extra overhead of learning assembly language programming. Written for high-level language programmers, Understanding the Machine fills in the low-level details of machine organization that are often left out of computer science and engineering courses. Learn: How the machine represents numbers, strings, and high-level data structures, so you'll know the inherent cost of using them. How to organize your data, so the machine can access it efficiently. How the CPU operates, so you can write code that works the way the machine does. How I/O devices operate, so you can maximize your application's performance when accessing those devices. How to best use the memory hierarchy to produce the fastest possible programs. Great code is efficient code. But before you can write truly efficient code, you must understand how computer systems execute programs and how abstractions in programming languages map to the machine's low-level hardware. After all, compilers don't write the best machine code; programmers do. This book gives you the foundation upon which all great software is built. NEW IN THIS EDITION, COVERAGE OF: Programming languages like Swift and Java Code generation on modern 64-bit CPUs ARM processors on mobile phones and tablets Newer peripheral devices Larger memory systems and large-scale SSDs

Explains how compilers translate high-level language source code (like code written in Python) into low-level machine code (code that the computer can understand) to help readers understand how to produce the best low-level, computer readable machine code. In the beginning, most software was written in assembly, the CPU's low-level language, in order to achieve acceptable performance on relatively slow hardware. Early programmers were sparing in their use of high-level language code, knowing that a high-level language compiler would generate crummy, low-level machine code for their software. Today, however, many programmers write in high-level languages like Python, C/C++/C#, Java, Swift. The result is often sloppy, inefficient code. But you don't need to give up the productivity and portability of high-level languages in order to produce more efficient software. In this second volume of the Write Great Code series, you'll learn: • How to analyze the output of a compiler to verify that your code does, indeed, generate good machine code • The types of machine code statements that compilers typically generate for common control structures, so you can choose the best statements when writing HLL code • Just enough 80x86 and PowerPC assembly language to read compiler output • How compilers convert various constant and variable objects into machine data, and how to use these objects to write faster and shorter programs NEW TO THIS EDITION, COVERAGE OF: • Programming languages like Swift and Java • Code generation on modern 64-bit CPUs • ARM processors on mobile phones and tablets • Stack-based architectures like the Java Virtual Machine • Modern language systems like the Microsoft Common Language Runtime With an understanding of how compilers work, you'll be able to write source code that they can translate into elegant machine code. That understanding starts right here, with Write Great Code, Volume 2: Thinking Low-Level, Writing High-Level.

Engineering Software, the third volume in the landmark Write Great Code series by Randall Hyde, helps you create readable and maintainable code that will generate awe from fellow programmers. The field of software engineering may value team productivity over individual growth, but legendary computer scientist Randall Hyde wants to make promising programmers into masters of their craft. To that end, Engineering Software--the latest volume in Hyde's highly regarded Write Great Code series--offers his signature in-depth coverage of everything from development methodologies and strategic productivity to object-oriented design requirements and system documentation. You'll learn: Why following the software craftsmanship model can lead you to do your best work How to utilize traceability to enforce consistency within your documentation The steps for creating your own UML requirements with use-case analysis How to leverage the IEEE documentation standards to create better software This advanced apprenticeship in the skills, attitudes, and ethics of quality software development reveals the right way to apply engineering principles to programming. Hyde will teach you the rules, and show you when to break them. Along the way, he offers illuminating insights into best practices while empowering you to invent new ones. Brimming with resources and packed with examples, Engineering Software is your go-to guide for writing code that will set you apart from your peers.

The pervasiveness of and universal access to modern Information and Communication Technologies has enabled a popular new paradigm in the dissemination of information, art, and ideas. Now, instead of relying on a finite number of content providers to control the flow of information, users can generate and disseminate their own content for a wider audience. Open Source Technology: Concepts, Methodologies, Tools, and Applications investigates examples and methodologies in user-generated and freely-accessible content available through electronic and online media. With applications in education, government, entertainment, and more, the technologies explored in these volumes will provide a comprehensive reference for web designers, software developers, and practitioners in a wide variety of fields and disciplines.

Computer science graduates often find software engineering knowledge and skills are more in demand after they join the industry. However, given the lecture-based curriculum present in academia, it is not an easy undertaking to deliver industry-standard knowledge and skills in a software engineering classroom as such lectures hardly engage or convince students. Overcoming Challenges in Software Engineering Education: Delivering Non-Technical Knowledge and Skills combines recent advances and best practices to improve the curriculum of software engineering education. This book is an essential reference source for researchers and educators seeking to bridge the gap between industry expectations and what academia can provide in software engineering education.

Professionals in the interdisciplinary field of computer science focus on the design, operation, and maintenance of computational systems and software. Methodologies and tools of engineering are utilized alongside computer applications to develop efficient and precise information databases. Computer Systems and Software Engineering: Concepts, Methodologies, Tools, and Applications is a comprehensive reference source for the latest scholarly material on trends, techniques, and uses of various technology applications and examines the benefits and challenges of these computational developments. Highlighting a range of pertinent topics such as utility computing, computer security, and information systems applications, this multi-volume book is ideally designed for academicians, researchers, students, web designers, software developers, and practitioners interested in computer systems and software engineering.

The three-volume set LNCS 5101-5103 constitutes the refereed proceedings of the 8th International Conference on Computational Science, ICCS 2008, held in Krakow, Poland in June 2008. The 167 revised papers of the main conference track presented together with the abstracts of 7 keynote talks and the 100 revised papers from 14 workshops were carefully reviewed and selected for inclusion in the three volumes. The main conference track was divided into approximately 20 parallel sessions addressing topics such as e-science applications and systems, scheduling and load balancing, software services and tools, new hardware and its applications, computer networks, simulation of complex systems, image processing and visualization, optimization techniques, numerical linear algebra, and numerical algorithms. The second volume contains workshop papers related to various computational research areas, e.g.: computer graphics and geometric modeling, simulation of multiphysics multiscale systems, computational chemistry and its applications, computational finance and business intelligence, physical, biological and social networks, geocomputation, and teaching computational science. The third volume is mostly related to computer science topics such as bioinformatics' challenges to computer science, tools for program development and analysis in computational science, software engineering for large-scale computing, collaborative and cooperative environments, applications of workflows in computational science, as well as intelligent agents and evolvable systems.

C# Deconstructed answers a seemingly simply question: Just what is going on, exactly, when you run C# code on the .NET Framework? To answer this question we will dig ever deeper into the structure of the C# language and the onion-skin abstraction layers of the .NET Framework that underpins it. We’ll follow the execution thread downwards, first to MSIL (Microsoft Intermediate Language) then down through just-in-time compilation into Machine Code before finally seeing the results executed at the hardware level. The aim of this deep-dive is to provide you with a much more rounded knowledge of the environment within which you code exists. As a managed language, it’s best-practice to let the Framework deal with device interaction but you’ll find the experience of taking the cover off once in a while a very rewarding one that will greatly enrich your appreciate of the C# language and the way in which in functions.