Discrete Mathematics for Computer Science

An Example-Based Introduction
2. Auflage 2027
ISBN: 978-1-041-15435-8
Verlag: CRC Press

Buch, Englisch, 416 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 516 g

Discrete Mathematics for Computer Science: An Example-Based Introduction, Second Edition, is intended for a first- or second-year discrete mathematics course for computer science and information systems majors. It covers many important mathematical topics essential for these students, such as algorithms, number representations, logic, set theory, Boolean algebra, functions, combinatorics, algorithmic complexity, graphs, trees, and relations with their applications to databases.

Features:

- Especially useful for community college courses; ideal as a first- or second-year textbook for computer science and information systems majors, or as a general introduction to discrete mathematics

- Written to be accessible to those with a limited mathematics background, and to aid with the transition to abstract thinking

- Filled with over 200 worked examples, boxed for easy reference, and over 200 end-of-chapter problems, many with multiple parts

- Contains approximately 40 simple algorithms, highlighted for easy reference, to aid students in becoming proficient with algorithm control structures and pseudocode

- Includes an appendix on basic circuit design, which provides a real-world motivational example for computer science majors by drawing on multiple topics covered in the book to design a circuit that adds two eight-digit binary numbers

New to the Second Edition:

- A new section at the end of each chapter that implements algorithms in Python and illustrates mathematical concepts with working code, introducing the essential Python skills needed by students who are new to the language

- Expanded computational content, including experimental time-complexity analysis; Python implementation of graph algorithms such as Dijkstra’s, Hierholzer’s, and Warshall’s algorithms, with NetworkX visualization; and implementation of binary search trees, AVL trees, B-trees, and binary heaps

- A new chapter on relations and their applications in databases, linking set theory to entity-relationship models, normalization, and an introduction to SQL

- Many additional end-of-chapter problems, including Python programming exercises

- A downloadable PDF solution manual containing solutions to the end-of-chapter problems

- Python workbooks containing all the Python code included in the textbook, together with solutions to the Python exercises, freely downloadable at: https://github.com/lyndaSm/Discrete_Mathematics_for_Computer_Science

Zielgruppe

Undergraduate Advanced and Undergraduate Core

Autoren/Hrsg.

Pierre Fortney, Jon

Smail, Linda

Inhaltsverzeichnis

1. Introduction to Algorithms 2. Number Representations 3. Logic 4. Set Theory 5. Boolean Algebra 6. Functions 7. Counting and Combinatorics 8. Algorithmic Complexity 9. Graph Theory 10. Trees 11. Relations and Their Applications in Databases

Über Autor(innen)

Jon Pierre Fortney graduated from the University of Pennsylvania in 1996 with a B.A. in Mathematics and Actuarial Science and a B.S.E. in Chemical Engineering. Before returning to graduate school, he worked as both an actuarial analyst and an environmental engineer. He graduated from Arizona State University in 2008 with a Ph.D. in Mathematics, specializing in Geometric Mechanics. He has almost twenty years of university-level teaching experience, including ten years in the Middle East. Dr. Fortney is currently a faculty member at the University of Maryland, Baltimore County (UMBC). Dr. Fortney is devoted to teaching and pedagogy. He is the author or coauthor of three undergraduate-level mathematics textbooks: A Visual Introduction to Differential Forms and Calculus on Manifolds, Discrete Mathematics for Computer Science: An Example-Based Introduction, and, with Dr. Linda Smail, Calculus for Business and Economics: An Example- Based Introduction. His many years of experience teaching business calculus helped shape the content and example-based approach of the latter book.

Linda Smail graduated from the University of Batna, Algeria, in 1998 with a B.S. in Mathematics. She then earned an M.S. in Analysis and Applied Mathematics from Marnela-Vallée University, France, and completed her Ph.D. in Applied Mathematics at the same institution in 2004, specializing in Bayesian networks. With more than twenty years of university-level teaching experience, including over fifteen years in the Middle East, Dr. Smail has demonstrated a strong commitment to education and research. In 2017, she furthered her education by earning a B.S. in Mathematics and Economics from the London School of Economics. Dr. Smail has developed and taught numerous courses in discrete mathematics, business mathematics, statistics, economics, and Python programming. She has designed Python courses, computational learning materials, programming exercises, and practical examples that help students connect mathematical concepts with real-world applications. She also uses Python extensively in her research for data analysis, statistical modeling, machine learning, Bayesian network analysis, and implementing computational methods. Together with Dr. Fortney, Dr. Smail is the coauthor of Calculus for Business and Economics: An Example-Based Introduction. She is currently a faculty member at Zayed University, where she continues to contribute to the academic community through teaching, research, curriculum development, and student mentorship.