Theoretical computer science treats any computational subject for which a good model can be created. Research on formal models of computation was initiated in the 1930s and 1940s by Turing, Post, Kleene, Church, and others. In the 1950s and 1960s programming languages, language translators, and operating systems were under development and therefore became both the subject and basis for a great deal of theoretical work. The power of computers of this period was limited by slow processors and small amounts of memory, and thus theories (models, algorithms, and analysis) were developed to explore the efficient use of computers as well as the inherent complexity of problems. The former subject is known today as algorithms and data structures, the latter computational complexity.

The focus of theoretical computer scientists in the 1960s on languages is reflected in the first textbook on the subject,Formal Languages and Their Relation to Automata by John Hopcroft and Jeffrey Ullman. This influential book led to the creation of many language centered theoretical computer science courses; many introductory theory courses today continue to reflect the content of this book and the interests of theoreticians of the 1960s and early 1970s.

Although the 1970s and 1980s saw the development of models and methods of analysis directed at understanding the limits on the performance of computers, this attractive new material has not been made available at the introductory level. This book is designed to remedy this situation.

This book is distinguished from others on theoretical computer science by its primary focus on real problems, its emphasis on concrete models of machines and programming styles, and the number and variety of models and styles it covers. These include the logic circuit, the finitestate machine, the push down automaton, the random-access machine, memory hierarchies, the PRAM (parallel random-access machine), the VLSI (very large-scale integrated) chip, and a variety of parallel machines.