An Introduction To Computer Science Using C

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An Introduction to Computer Science Using C

This text is intended for an introductory course in computer science. The authors present a conceptual introduction to key concepts and methodologies of computer science. C is the language of instruction, and is integrated only as needed to highlight points and demonstrate concepts throughout the text. In addition to numerous exercises, laboratory activities are incorporated into each Chapter (after Chapter 1), leading students through an experimental approach to the concepts and techniques covered in the text.
Introduction to Computer Science with C++

Developed from the model used successfully in the Naps and Nance full-year texts in Pascal, this book combines Lambert and Nance's Understanding Programming and Problem Solving with C++ and Lambert and Naps's Understanding Program Design and Data Structures with C++ into a single CS1/CS2 text. Hence, Introduction to Computer Science with C++ solves the problem of where to begin CS2 that can occur when C++ is the teaching language. It also saves students money -- they don't have to buy two separate texts. This full-year introduction to CS1/CS2 features a gradual approach that covers problem solving and algorithm development while giving students a solid grounding in objects and classes. Throughout the book, a highly structured approach to programming produces programs that are easy to read, debug, and modify. Examples are carefully developed using pseudocode, structure charts, and module specifications. Programming Problems and Projects at the end of each chapter feature numerous programming assignments. They reflect a variety of areas (business, math, etc.) and ask students to build on programs written for earlier chapters, and to practice their communication skills.
Introduction to Computational Modeling Using C and Open-Source Tools

Introduction to Computational Modeling Using C and Open-Source Tools presents the fundamental principles of computational models from a computer science perspective. It explains how to implement these models using the C programming language. The software tools used in the book include the Gnu Scientific Library (GSL), which is a free software library of C functions, and the versatile, open-source GnuPlot for visualizing the data. All source files, shell scripts, and additional notes are located at science.kennesaw.edu/~jgarrido/comp_models The book first presents an overview of problem solving and the introductory concepts, principles, and development of computational models before covering the programming principles of the C programming language. The author then applies programming principles and basic numerical techniques, such as polynomial evaluation, regression, and other numerical methods, to implement computational models. He also discusses more advanced concepts needed for modeling dynamical systems and explains how to generate numerical solutions. The book concludes with the modeling of linear optimization problems. Emphasizing analytical skill development and problem solving, this book helps you understand how to reason about and conceptualize the problems, generate mathematical formulations, and computationally visualize and solve the problems. It provides you with the foundation to understand more advanced scientific computing, including parallel computing using MPI, grid computing, and other techniques in high-performance computing.