The Craft of Programming
by John C. Reynolds
Publisher: Prentice Hall 1981
Number of pages: 434
The modern computer is so powerful that a casual knowledge of programming suffices for most of its users. However, a variety of circumstances can abruptly require a much deeper understanding: the need to structure a program carefully to avoid being overwhelmed by its complexity, the need to insure reliability beyond what can he achieved by debugging, or the need to utilize computing resources efficiently. Beyond such practical considerations, there is an inherent intellectual satisfaction in mastering the fundamental concepts of programming. The aim of this book is to provide such mastery concept by concept. For example, the reader is expected to understand proofs of correctness and order-of-magnitude time requirements for simple integer algorithms - such as log n exponentiation - before the concept of arrays is introduced. A similarly thorough understanding of array manipulating algorithms is expected before the introduction of procedures.
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by James M. Reneau - CreateSpace
Learn to program a computer without the jargon and complexity of many programming books. This book engages through media and then introduces the concepts of structured programming. You will learn to program as you make animations and games.
by Nils M Holm - Lulu Press
This book introduces the concept of functional programming, describes a language that fulfills all the requirements, and shows how to solve simple problems in it. The book shows how to apply these techniques to some problems of varying complexity.
by Lawrence C Paulson - University of Cambridge
This text teaches programming and presents some fundamental principles of computer science, especially algorithm design. The programming in this course is based on the language ML and mostly concerns the functional programming style.
by Karthik Naidu - GitBook
These are engineer's notes on problem solving. They are ideally suited as practice material for coding interviews. Each post has 5 sections: problem statement, examples, algorithm, code, test cases, and a discussion on time-complexity.