Personal homepage of F.D. Lewis in the Department of Computer Science at the University of Kentucky College of Engineering is no longer available. I changed the book's original URL to its mirror at the University of Colorado Denver.
This book contains the essentials of theoretical computer science
. There might be a bit more, but this is a broad introduction to the field. And, it is presented from a computer science viewpoint for computer scientists. It does not come from one of the strongholds of mathematics even though a great deal of mathematical logic lurks within.
This book covers some definitions of computing since readers must know what it is they are studying. So, several models of computation are presented including a RISC machine. And, the theory that ties it together is not omitted. Quickly following is a portion concerning things which are not computable (the unsolvability chapter) since readers also must know what they are not studying. In addition, the material on unsolvability is important for historic reasons as well as a being a mechanism for introducing concepts which aid in precise analytical thought. Besides, some of these concepts form an important portion of algorithm complexity.
At this point this book will get specific and looks at classes of machines that execute set recognition algorithms. As a counterpoint, this book also examines classes of grammars which generate these sets of strings. Pointers to applications such as circuit design, compiling, and translation are provided. These are very practical chapters since even though the material is presented as theory, applications abound.
The final fling is a study of how difficult it all was. This ties into algorithm analysis and is very central to many of our endeavors in computer science. The concepts here (in particular NP-completeness) intrude upon much of the practical work in business, government, and industry. This material is essentialif one is to know when to apply heuristics to problems.
This book was designed to be used in a one-semester course for senior computer science majors or first year masters students. (But there is enough material here for two quarters.) It covers the basics of the theory of computation and should provide some of the tools used in program verification, translation and compiling, and the analysis of algorithms. An effort was made to provide precise, logical, mathematical arguments with a minimum of pain. Whenever points could be made in the language of computer science, they were. Whenever something could be computed, the procedure was presented in algorithmic language. This is a text for computer scientists though all that will are welcome to indulge.