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This 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 introduced, demonstrating what can and cannot be computed efficiently at scale, helping programmers make informed judgements about the algorithms they use. The easy-to-read text assumes some basic experience in computer programming and familiarity in an object-oriented language, but not necessarily with Python.Topics and features:Includes introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective coursesProvides learning goals, review questions, and programming exercises in each chapter, as well as numerous examplesPresents a primer on Python for those coming from a different language backgroundAdds a new chapter on multiprocessing with Python using the DragonHPC multinode implementation of multiprocessing (includes a tutorial)Reviews the use of hashing in sets and maps, and examines binary search trees, tree traversals, and select graph algorithmsOffers downloadable programs and supplementary files at an associated website to help studentsStudents of computer science will find this clear and concise textbook 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.Dr. Kent D. Lee is a Professor Emeritus of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer books, Python Programming Fundamentals, and Foundations of Programming Languages.Dr. Steve Hubbard is a Professor Emeritus of Mathematics and Computer Science at Luther College.

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.

This clearly written 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. Features: includes review questions and solved practice exercises, with supplementary code and support files available from an associated website; provides the foundations for understanding how the syntax of a language is formally defined by a grammar; examines assembly language programming using CoCo; introduces C++, Standard ML, and Prolog; describes the development of a type inference system for thelanguage Small.

This 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 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. 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 from a different language background.

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. 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.

Computer programming is a skill that can bring great enjoyment from the creativity involved in designing and implementing a solution to a problem. This classroom-tested and easy-to-follow textbook teaches the reader how to program using Python, an accessible language which can be learned incrementally. Through an extensive use of examples and practical exercises, students will learn to recognize and apply abstract patterns in programming, as well as how to inspect the state of a program using a debugger tool. Features: contains numerous examples and solved practice exercises designed for an interactive classroom environment; highlights several patterns which commonly appear in programs, and presents exercises that reinforce recognition and application of these patterns; introduces the use of a debugger, and includes supporting material that reveals how programs work; presents the Tkinter framework for building graphical user interface applications and event-driven programs; provides helpful additional resources for instructors at the associated website: http://cs.luther.edu/~leekent/CS1. This hands-on textbook for active learning in the classroom will enable undergraduates in computer science to develop the necessary skills to begin developing their own programs. It employs Python as the introductory language due to the wealth of support available for programmers.

Programming Languages: An Active Learning Approach introduces students to three programming paradigms: object-oriented/imperative languages using C++ and Ruby, functional languages using Standard ML, and logic programming using Prolog. This interactive textbook is intended to be used in and outside of class. Each chapter follows a pattern of presenting a topic followed by a practice exercise or exercises that encourage students to try what they have just read. This textbook is best-suited for students with a 2-3 course introduction to imperative programming. Key Features: (1) Accessible structure guides the student through various programming languages. (2) Seamlessly integrated practice exercises. (3) Classroom-tested. (4) Online support materials. Advance praise: “The Programming Languages book market is overflowing with books, but none like this. In many ways, it is precisely the book I have been searching for to use in my own programming languages course. One of the main challenges I perpetually face is how to teach students to program in functional and logical languages, but also how to teach them about compilers. This book melds the two approaches very well.” -- David Musicant, Carleton College