《计算的本质：深入剖析程序和计算机》借助Ruby全面介绍计算理论和编程语言的设计。作者注重实用性，不仅尽量抛开复杂难懂的数学符号，而且特别选用简单快捷的编程语言Ruby，在读者熟知的背景知识下，以明晰的可工作代码阐明形式语义、自动机理论，以及通过lambda演算进行函数式编程等计算机科学知识，并为让其自行探索做足准备。
本书适合计算机科学系学生，以及熟知现代编程语言，想要系统地学习计算机科学知识的程序员、软件工程师阅读参考。

Computability and complexity theory should be of central concern to practitioners as well as theorists. Unfortunately, however, the field is known for its impenetrability. Neil Jones's goal as an educator and author is to build a bridge between computability and complexity theory and other areas of computer science, especially programming. In a shift away from the Turing machine- and Gödel number-oriented classical approaches, Jones uses concepts familiar from programming languages to make computability and complexity more accessible to computer scientists and more applicable to practical programming problems.<br /> <br /> According to Jones, the fields of computability and complexity theory, as well as programming languages and semantics, have a great deal to offer each other. Computability and complexity theory have a breadth, depth, and generality not often seen in programming languages. The programming language community, meanwhile, has a firm grasp of algorithm design, presentation, and implementation. In addition, programming languages sometimes provide computational models that are more realistic in certain crucial aspects than traditional models.<br /> <br /> New results in the book include a proof that constant time factors do matter for its programming-oriented model of computation. (In contrast, Turing machines have a counterintuitive "constant speedup" property: that almost any program can be made to run faster, by any amount. Its proof involves techniques irrelevant to practice.) Further results include simple characterizations in programming terms of the central complexity classes PTIME and LOGSPACE, and a new approach to complete problems for NLOGSPACE, PTIME, NPTIME, and PSPACE, uniformly based on Boolean programs.<br /> <br /> Foundations of Computing series