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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:
"Lethal FrontierS" is one of the first samples of Soviet scholarship on nuclear strategy readily available to Western readers. A rising star in the Soviet foreign policy establishment, Arbatov offers a remarkable view of the evaluation of U.S. nuclear policy and strategy. This scholarly book is free of the ideological constraints and negative effects of excessive Soviet secrecy so often characterizing Soviet works on this subject. The author begins by tracing the buildup of U.S. nuclear and conventional forces during the Kennedy and Johnson administrations, and examines initial U.S. reactions to the achievement of strategic nuclear parity by the Soviet Union in the late 1960s and early 1970s. From notions of flexible response, to the Schlesinger doctrine, and ideas of fighting a limited nuclear war, Arbatov argues that the U.S. national security establishment has had enormous difficulty in reconciling itself with Soviet strategic parity. Consequently, U.S. strategy and arms programs have invariably collided with and contradicted the arms control process and efforts to decrease U.S.-Soviet tensions. In light of this, and of the new Soviet approach to security, Arbatov observes the challenges lying ahead in the new era of Soviet-American relations.
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.
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:
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 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 courses Provides learning goals, review questions, and programming exercises in each chapter, as well as numerous examples Presents a primer on Python for those coming from a different language background Adds 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 algorithms Discusses such advanced topics as membership structures, heaps, balanced binary search trees, B-trees and heuristic search Offers downloadable programs and supplementary files at an associated website to help students Students 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.
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