Annual Review in Automatic Programming is a collection of papers presented at the Working Conference on Automatic Programming of Digital Computers held in Brighton, UK, on April 1-3, 1959. Contributors focus on developments in automatic programming and cover topics ranging from automatic coding for TREAC to the PEGASUS and MERCURY autocodes, automatic programming of DEUCE, and the philosophy of programming. Business applications of automatic programming are also discussed. This book is comprised of 17 chapters and begins with a review of future trends in automatic programming, focusing on the environment of a computer as well as machine languages and automatic codes. The features of existing automatic programming languages are also described, along with the advantages and disadvantages of such languages. The next chapter presents some of the arguments in favor of standardized notations for programming, mainly with reference to scientific problems. The reader is also introduced to the Mark 5 system of automatic coding for TREAC; assembly, interpretive, and conversion programs for PEGASUS; and application of formula translation to the automatic coding of ordinary differential equations. The final chapter describes a machine designed for the manufacture of accurate models for wind tunnel tests. This monograph will be of interest to computer programmers, computer manufacturers, computer users, and university students.

With this visual guide to computer programming for beginners, it has never been easier to learn how to code. Coding skills are in high demand and the need for programmers is still growing. Covering three of the most popular languages for new coders, this book uses a graphic method to break complex subjects into user-friendly chunks, bringing essential skills within easy reach. Each chapter contains tutorials on practical projects designed to teach you the main applications of each language, such as building websites, creating games, and designing apps. The book also looks at many of the main coding languages that are out there, outlining the key applications of each language, so you can choose the right language for you. You'll learn to think like a programmer by breaking a problem down into parts, before turning those parts into lines of code. Short, easy-to-follow steps then show you, piece by piece, how to build a complete program. There are challenges for you to tackle to build your confidence before moving on. Written by a team of expert coders and coding teachers, Beginner's Step-by-Step Coding Course is the ideal way to get to set you on the road to code.

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

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