John S. Conery - Böcker

An Active Learning Approach to Teaching the Main Ideas in Computing Explorations in Computing: An Introduction to Computer Science and Python Programming teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. Tbook gives beginning students an introduction to computer science concepts and computer programming. Designed for CS0 and CS1 courses, it is very well suited for alternative lecture styles, including flipped classrooms.Prepares Students for Advanced Work in Computer ScienceA revised and updated version of the author’s Explorations in Computing: An Introduction to Computer Science, this text incorporates two major differences. It now uses Python, instead of Ruby, as the lab software so that students can seamlessly transition from introductory projects to more advanced studies in later courses. The book also introduces Python programming, providing students with sufficient programming skills so they can implement their own programs.Practical, Step-by-Step ProjectsThe interactive lab projects in each chapter allow students to examine important ideas in computer science, particularly how algorithms offer computational solutions to problems. Students can type expressions, view results, and run experiments that help them understand the concepts in a hands-on way.Web ResourcesThe Python software modules for each lab project are available on the author’s website. The modules include data files and sample Python code that students can copy and modify. In addition, the site provides a lab manual of installation instructions and tips for editing programs and running commands in a terminal emulator.

Based on the author’s introductory course at the University of Oregon, Explorations in Computing: An Introduction to Computer Science focuses on the fundamental idea of computation and offers insight into how computation is used to solve a variety of interesting and important real-world problems. Taking an active learning approach, the text encourages students to explore computing ideas by running programs and testing them on different inputs. It also features illustrations by Phil Foglio, winner of the 2009 and 2010 Hugo Award for Best Graphic Novel.Classroom-Tested MaterialThe first four chapters introduce key concepts, such as algorithms and scalability, and hone practical lab skills for creating and using objects. In the remaining chapters, the author covers "divide and conquer" as a problem solving strategy, the role of data structures, issues related to encoding data, computer architecture, random numbers, challenges for natural language processing, computer simulation, and genetic algorithms. Through a series of interactive projects in each chapter, students can experiment with one or more algorithms that illustrate the main topic. Requiring no prior experience with programming, these projects show students how algorithms provide computational solutions to real-world problems. Web ResourceThe book’s website at www.cs.uoregon.edu/eic presents numerous ancillaries. The lab manual offers step-by-step instructions for installing Ruby and the RubyLabs gem with Windows XP, Mac OS X, and Linux. The manual includes tips for editing programs and running commands in a terminal emulator. The site also provides online documentation of all the modules in the RubyLabs gem. Once the gem is installed, the documentation can be read locally by a web browser.After working through the in-depth examples in this textbook, students will gain a better overall understanding of what computer science is about and how computer scientists think about problems.

This book is an updated version of my Ph.D. dissertation, The AND/OR Process Model for Parallel Interpretation of Logic Programs. The three years since that paper was finished (or so I thought then) have seen quite a bit of work in the area of parallel execution models and programming languages for logic programs. A quick glance at the bibliography here shows roughly 50 papers on these topics, 40 of which were published after 1983. The main difference between the book and the dissertation is the updated survey of related work. One of the appendices in the dissertation was an overview of a Prolog implementation of an interpreter based on the AND/OR Process Model, a simulator I used to get some preliminary measurements of parallelism in logic programs. In the last three years I have been involved with three other implementations. One was written in C and is now being installed on a small multiprocessor at the University of Oregon. Most of the programming of this interpreter was done by Nitin More under my direction for his M.S. project. The other two, one written in Multilisp and the other in Modula-2, are more limited, intended to test ideas about implementing specific aspects of the model. Instead of an appendix describing one interpreter, this book has more detail about implementation included in Chapters 5 through 7, based on a combination of ideas from the four interpreters.