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This easy-to-follow and classroom-tested textbook guides the reader through the fundamentals of programming with Python, an accessible language which can be learned incrementally. This revised and updated new edition will teach students how to recognize and apply abstract patterns in programming through the extensive use of illustrative examples and practical exercises. The book also demonstrates the benefit of using a debugger to inspect the state of a program while it is executing. Topics and features: Includes numerous examples and practice exercises throughout the text, with additional exercises, solutions and review questions at the end of each chapter Highlights the patterns which frequently appear when writing programs, reinforcing the application of these patterns for problem-solving through practice exercises Introduces the use of a debugger tool to inspect a program, enabling students to discover for themselves how programs work and enhance their understanding Presents the Tkinter framework for building graphical user interface applications and event-driven programs Provides instructional videos and additional information for students, as well as support materials for instructors, at an associated website Ideal for introductory programming courses for undergraduates in computer science, this hands-on textbook for interactive classroom learning will help students to develop the necessary skills to begin writing their own programs. Due to the wealth of support material available, Python is selected as a good first language with little “overhead” in learning to write simple programs. Dr. Kent D. Lee is Professor of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the forthcoming Springer textbooks Data Structures and Algorithms with Python and Foundations of Programming Languages.

Computer science. --- Programming languages (Electronic computers). --- Computer Science. --- Programming Languages, Compilers, Interpreters. --- Computer languages --- Computer program languages --- Computer programming languages --- Machine language --- Electronic data processing --- Languages, Artificial --- Informatics --- Science --- Python (Computer program language). --- Python. --- Scripting languages (Computer science) --- Python (Computer program language)

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This clearly written and simple to follow textbook introduces the reader to the three styles of programming, examining object-oriented/imperative, functional, and logic programming. The focus of the text moves from highly prescriptive languages to very descriptive languages, demonstrating the many and varied ways in which we can think about programming. Designed for interactive learning both inside and outside of the classroom, each programming paradigm is highlighted through the implementation of a non-trivial programming language, demonstrating when each language may be appropriate for a given problem. Topics and features: Includes review questions and solved practice exercises, with supplementary code and support files available from an associated website Discusses the historical background to the models of computation used in implementing the programming languages we use today Provides the foundations for understanding how the syntax of a language is formally defined by a grammar Examines assembly language programming through a series of examples, using a Python Virtual Machine implementation called CoCo Introduces object-oriented languages through examples in C++, functional programming with Standard ML, and programming using the logic language Prolog Describes the development and implementation of a type inference system for the full-featured functional language Small Suitable for stude nts of computer science at the undergraduate level, this engaging textbook takes an active learning approach to the next stage in understanding programming languages, once the reader has established some familiarity with an imperative language and the basics of data structures.

Computer science. --- Programming languages (Electronic computers). --- Computer Science. --- Programming Languages, Compilers, Interpreters. --- Informatics --- Science --- Programming languages (Electronic computers) --- Computer languages --- Computer program languages --- Computer programming languages --- Machine language --- Electronic data processing --- Languages, Artificial

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This easy-to-follow and classroom-tested textbook guides the reader through the fundamentals of programming with Python, an accessible language which can be learned incrementally. This revised and updated new edition will teach students how to recognize and apply abstract patterns in programming through the extensive use of illustrative examples and practical exercises. The book also demonstrates the benefit of using a debugger to inspect the state of a program while it is executing. Topics and features: Incudes numerous examples and practice exercises throughout the text, with additional exercises, solutions and review questions at the end of each chapter Highlights the patterns which frequently appear when writing programs, reinforcing the application of these patterns for problem-solving through practice exercises Introduces the use of a debugger tool to inspect a program, enabling students to discover for themselves how programs work and enhance their understanding Presents the Tkinter framework for building graphical user interface applications and event-driven programs Provides instructional videos and additional information for students, as well as support materials for instructors, at an associated website Ideal for introductory programming courses for undergraduates in computer science, this hands-on textbook for interactive classroom learning will help students to develop the necessary skills to begin writing their own programs. Due to the wealth of support material available, Python is selected as a good first language with little “overhead” in learning to write simple programs. Dr. Kent D. Lee is Professor of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the forthcoming Springer textbooks Data Structures and Algorithms with Python and Foundations of Programming Languages.

Computer science --- Programming --- Python (informatica) --- computers --- programmeertalen --- computerkunde

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This clearly written textbook provides an accessible introduction to the three programming paradigms of object-oriented/imperative, functional, and logic programming. Highly interactive in style, the text encourages learning through practice, offering test exercises for each topic covered. Review questions and programming projects are also presented, to help reinforce the concepts outside of the classroom. This updated and revised new edition features new material on the Java implementation of the JCoCo virtual machine. Topics and features: Includes review questions and solved practice exercises, with supplementary code and support files available from an associated website Presents an historical perspective on the models of computation used in implementing the programming languages used today Provides the foundations for understanding how the syntax of a language is formally defined by a grammar Illustrates how programs execute at the level of assembly language, through the implementation of a stack-based Python virtual machine called JCoCo and a Python disassembler Introduces object-oriented languages through examples in Java, functional programming with Standard ML, and programming using the logic language Prolog Describes a case study involving the development of a compiler for the high level functional language Small, a robust subset of Standard ML Undergraduate students of computer science will find this engaging textbook to be an invaluable guide to the skills and tools needed to become a better programmer. While the text assumes some background in an imperative language, and prior coverage of the basics of data structures, the hands-on approach and easy to follow writing style will enable the reader to quickly grasp the essentials of programming languages, frameworks, and architectures. Dr. Kent D. Lee is Professor of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer textbooks Python Programming Fundamentals and Data Structures and Algorithms with Python.

Mathematics --- Applied physical engineering --- Engineering sciences. Technology --- Computer science --- Programming --- Computer architecture. Operating systems --- Computer. Automation --- machinetalen --- ICT (informatie- en communicatietechnieken) --- Python (informatica) --- machine learning --- computers --- economie --- programmeren (informatica) --- programmeertalen --- wiskunde --- Java (informatica) --- ingenieurswetenschappen --- computerkunde

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This clearly structured and easy to read textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by motivating examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. The text assumes some basic experience in computer programming and familiarity in an object-oriented language, but not necessarily with Python. Topics and features: Includes both introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses provided in the preface Provides learning goals, review questions and programming exercises in each chapter, as well as numerous illustrative examples Offers downloadable programs and supplementary files at an associated website, with instructor materials available from the author Presents a primer on Python for those coming from a different language background Reviews the use of hashing in sets and maps, along with an examination of binary search trees and tree traversals, and material on depth first search of graphs Discusses topics suitable for an advanced course, such as membership structures, heaps, balanced binary search trees, B-trees and heuristic search Students of computer science will find this clear and concise textbook to be invaluable for undergraduate courses on data structures and algorithms, at both introductory and advanced levels. The book is also suitable as a refresher guide for computer programmers starting new jobs working with Python.

Complex analysis --- Computer science --- Programming --- Computer architecture. Operating systems --- Computer. Automation --- Python (informatica) --- complexe analyse (wiskunde) --- computers --- informatica --- programmeren (informatica) --- database management --- programmatielogica --- algoritmen