Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts. Benjamin C. Pierce received his doctoral degree from Carnegie Mellon University.Contents : Tutorial. Applications. Further Reading.

"This is an advanced 2001 textbook on modal logic, a field which caught the attention of computer scientists in the late 1970s. Researchers in areas ranging from economics to computational linguistics have since realised its worth. The book is for novices and for more experienced readers, with two distinct tracks clearly signposted at the start of each chapter. The development is mathematical; prior acquaintance with first-order logic and its semantics is assumed, and familiarity with the basic mathematical notions of set theory is required. The authors focus on the use of modal languages as tools to analyze the properties of relational structures, including their algorithmic and algebraic aspects, and applications to issues in logic and computer science such as completeness, computability and complexity are considered. Three appendices supply basic background information and numerous exercises are provided. Ideal for anyone wanting to learn modern modal logic."--Publisher's website.

With their intuitive graphical approach and expressive analysis techniques, Petri nets are suitable for a wide range of applications and teaching scenarios, and they have gained wide acceptance as a modeling technique for computer science-based systems. This book is a clear, thorough introduction to Petri nets. The explanations are supported throughout with fully integrated graphical illustrations, with only the analysis and verification presented in a formal manner. The author clearly explains the core of each related topic, leaving the reader to explore other sources for further details. The book will be suitable for students of computer science and related subjects. The book includes exercises and the solutions are available online.

类型理论在程序设计语言的发展中起着举足轻重的作用，成熟的类型系统可以帮助完善程序设计本身，帮助运行系统检查程序中的语义错误。 要理解类型系统在程序设计语言中发挥的作用，本书将是首选读物。本书内容覆盖基本操作语义及其相关证明技巧、无类型lambda演算、简单类型系统、全称多态和存在多态、类型重构、子类型化、囿界量词、递归类型、类型算子等内容。本书既注重内容的广度，也注重内容的深度，实用性强。在引入语言的语法对象时先举例，然后给出形式定义及基本证明，在对理论的进一步研究后给出了类型检查算法，并对每种算法都给出了OCaml程序的具体实现。本书对类型理论中的概念都有详细的阐述，为读者提供了一个进一步理论学习的基础。本书内容广泛，读者可以根据自己的需要有选择地深入阅读。 本书适合从事程序设计的研究人员和开发人员，以及程序设计语言和类型理论的研究人员阅读。可作为计算机专业高年级学生、研究生的学习教材。

《计算理论导引（原书第3版）》由计算理论领域的知名权威 Michael Sipser 所撰写。他以独特的视角，系统地介绍了计算理论的三个主要内容：自动机与语言、可计算性理论和计算复杂性理论。作者以清新的笔触、生动的语言给出了宽泛的数学原理，而没有拘泥于某些低层次的细节。在证明之前，均有“证明思路”，帮助读者理解数学形式下蕴涵的概念。本书可作为计算机专业高年级本科生和研究生的教材，也可作为教师和研究人员的参考书。

Gain a clear understanding of even the most complex, highly theoretical computational theory topics in the approachable presentation found only in the market-leading INTRODUCTION TO THE THEORY OF COMPUTATION, 3E. The number one choice for today's computational theory course, this revision continues the book's well-know, approachable style with timely revisions, additional practice, and more memorable examples in key areas. A new first-of-its-kind theoretical treatment of deterministic context-free languages is ideal for a better understanding of parsing and LR(k) grammars. You gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs. INTRODUCTION TO THE THEORY OF COMPUTATION, 3E's comprehensive coverage makes this a valuable reference for your continued studies in theoretical computing.

本书从为什么学习程序设计语言入手，深入细致地讲解了命令式语言的主要结构及其设计与实现，内容涉及变量、数据类型、表达式和赋值语句、控制语句、子程序、数据抽象机制、支持面向对象程序设计（继承和动态方法绑定）、并发和异常处理等方面。最后两章介绍了函数式程序设计语言和逻辑程序设计语言。 本书内容丰富，剖析透彻，被美国和加拿大多所高等院校采用作为教材。本书既可用做高等院校计算机及相关专业本科生程序设计语言课程的教材和参考书，也可供程序设计人员参考。

For sophomore/junior-level courses in Programming Languages, Comparative Programming Languages, Language Design, and Organization of Programming Languages, in departments of Computer Science and Computer Engineering. Comprehensive in approach, this text explores the major issues in both design and implementation of modern programming languages and provides a basic introduction to the underlying theoretical models on which these languages are based. It focuses on the underlying software and hardware architecture that guides language design, helping students understand why certain decisions are more rational than others in building a program. The emphasis throughout is on fundamental concepts-students learn important ideas, not minor language differences-but several languages are highlighted in sufficient detail to enable students to write programs that demonstrate the relationship between a source program and its execution behavior, without having to purchase separate language reference manuals.

《可计算性与计算复杂性导引(第3版)》是学习计算理论的教材和参考书，内容包括三部分：可计算性、形式语言与自动机、计算复杂性，主要介绍几种计算模型及它们的等价性，函数、谓词和语言的可计算性等基本概念，形式语言及其对应的自动机模型，时间和空间复杂性，NP完全性等。 《可计算性与计算复杂性导引(第3版)》可作为计算机专业本科生和研究生的教材，也可作为从事计算机科学技术的研究和开发人员的参考书，还可作为对计算理论感兴趣的读者的入门读物。

This classic book on formal languages, automata theory, and computational complexity has been updated to present theoretical concepts in a concise and straightforward manner with the increase of hands-on, practical applications. This new edition comes with Gradiance, an online assessment tool developed for computer science. Gradiance is the most advanced online assessment tool developed for the computer science discipline. With its innovative underlying technology, Gradiance turns basic homework assignments and programming labs into an interactive learning experience for students. By using a series of "root questions" and hints, it not only tests a student's capability, but actually simulates a one-on-one teacher-student tutorial that allows for the student to more easily learn the material. Through the programming labs, instructors are capable of testing, tracking, and honing their students' skills, both in terms of syntax and semantics, with an unprecedented level of assessment never before offered. For more information about Gradiance, please visit www.aw.com/gradiance.