Discovering Computer Science - Jessen Havill

Discovering Computer Science

Interdisciplinary Problems, Principles, and Python Programming

(Autor)

Buch | Hardcover
542 Seiten
2020 | 2nd edition
Chapman & Hall/CRC (Verlag)
978-0-367-61335-8 (ISBN)
209,95 inkl. MwSt
Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming introduces computational problem solving as a vehicle of discovery in a wide variety of disciplines.
"Havill's problem-driven approach introduces algorithmic concepts in context and motivates students with a wide range of interests and backgrounds."




-- Janet Davis

, Associate Professor and Microsoft Chair of Computer Science, Whitman College "This book looks really great and takes exactly the approach I think should be used for a CS 1 course. I think it really fills a need in the textbook landscape."




--

Marie desJardins, Dean of the College of Organizational, Computational, and Information Sciences, Simmons University"Discovering Computer Science is a refreshing departure from introductory programming texts, offering students a much more sincere introduction to the breadth and complexity of this ever-growing field."




--

James Deverick, Senior Lecturer, The College of William and Mary"This unique introduction to the science of computing guides students through broad and universal approaches to problem solving in a variety of contexts and their ultimate implementation as computer programs."




--

Daniel Kaplan, DeWitt Wallace Professor, Macalester College
Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming

is a problem-oriented introduction to computational problem solving and programming in Python, appropriate for a first course for computer science majors, a more targeted disciplinary computing course or, at a slower pace, any introductory computer science course for a general audience.Realizing that an organization around language features only resonates with a narrow audience, this textbook instead connects programming to students’ prior interests using a range of authentic problems from the natural and social sciences and the digital humanities. The presentation begins with an introduction to the problem-solving process, contextualizing programming as an essential component. Then, as the book progresses, each chapter guides students through solutions to increasingly complex problems, using a spiral approach to introduce Python language features.

The text also places programming in the context of fundamental computer science principles, such as abstraction, efficiency, testing, and algorithmic techniques, offering glimpses of topics that are traditionally put off until later courses.

This book contains 30 well-developed independent projects that encourage students to explore questions across disciplinary boundaries, over 750 homework exercises, and 300 integrated reflection questions engage students in problem solving and active reading.

The accompanying website — https://www.discoveringcs.net — includes more advanced content, solutions to selected exercises, sample code and data files, and pointers for further exploration.

Jessen Havill is a Professor of Computer Science at Denison University. He has been teaching courses across the computer science curriculum for almost thirty years, and was awarded the College's highest teaching honor, the Charles A. Brickman Teaching Excellence Award, in 2013. Although his primary expertise is in the development and analysis of online algorithms, Dr. Havill has spent many years collaborating with colleagues across the curriculum to develop interdisciplinary academic opportunities for students. From 2016-2019, he became the founding Director of Denison University's interdisciplinary Data Analytics program. Dr. Havill earned his bachelor's degree from Bucknell University and his Ph.D. in computer science from The College of William and Mary.

Preface

Acknowledgments

About the author

How to Solve It

UNDERSTAND THE PROBLEM

DESIGN AN ALGORITHM

WRITE A PROGRAM

LOOK BACK

SUMMARY AND FURTHER DISCOVERY

Visualizing Abstraction

DATA ABSTRACTION

DRAWING FLOWERS AND PLOTTING EARTHQUAKES

FUNCTIONAL ABSTRACTION

PROGRAMMING IN STYLE

A RETURN TO FUNCTIONS

SCOPE AND NAMESPACES

SUMMARY AND FURTHER DISCOVERY

Inside a Computer

COMPUTERS ARE DUMB

EVERYTHING IS BITS

COMPUTER ARITHMETIC

BINARY ARITHMETIC

THE UNIVERSAL MACHINE

Growth and Decay

ACCUMULATORS

DATA VISUALIZATION

CONDITIONAL ITERATION

CONTINUOUS MODELS

NUMERICAL ANALYSIS

SUMMING UP

FURTHER DISCOVERY

PROJECTS

Forks in the Road
RANDOM WALKS

PSEUDORANDOM NUMBER GENERATORS

SIMULATING PROBABILITY DISTRIBUTIONS

BACK TO BOOLEANS

DEFENSIVE PROGRAMMING

GUESS MY NUMBER

SUMMARY AND FURTHER DISCOVERY

PROJECTS

Text, Documents, and DNA

FIRST STEPS

TEXT DOCUMENTS

A CONCORDANCE

WORD FREQUENCY TRENDS

COMPARING TEXTS

TIME COMPLEXITY

COMPUTATIONAL GENOMICS

SUMMARY AND FURTHER DISCOVERY

PROJECTS

Data Analysis

SUMMARY STATISTICS

WRANGLING DATA

TALLYING FREQUENCIES

READING TABULAR DATA

DESIGNING EFFICIENT ALGORITHMS

LINEAR REGRESSION

DATA CLUSTERING

SUMMARY AND FURTHER DISCOVERY

PROJECTS

Flatland

TABULAR DATA

THE GAME OF LIFE

DIGITAL IMAGES

SUMMARY AND FURTHER DISCOVERY

PROJECTS

Self-similarity and Recursion

FRACTALS

RECURSION AND ITERATION

THE MYTHICAL TOWER OF HANOI

RECURSIVE LINEAR SEARCH

DIVIDE AND CONQUER

LINDENMAYER SYSTEMS

9SUMMARY AND FURTHER DISCOVERY

PROJECTS

Organizing Data

BINARY SEARCH

SELECTION SORT

INSERTION SORT

EFFICIENT SORTING

TRACTABLE AND INTRACTABLE ALGORITHMS

SUMMARY AND FURTHER DISCOVERY

PROJECTS

Networks

MODELING WITH GRAPHS

SHORTEST PATHS

IT’S A SMALL WORLD

RANDOM GRAPHS

SUMMARY AND FURTHER DISCOVERY

PROJECTS

Object-oriented Design

SIMULATING AN EPIDEMIC

OPERATORS AND POLYMORPHISM

A FLOCKING SIMULATION

A STACK ADT

A DICTIONARY ADT

SUMMARY AND FURTHER DISCOVERY

PROJECTS

Bibliography

Appendix A ■ Python Library

Appendix B ■ Selected Exercise
Index

Erscheinungsdatum
Reihe/Serie Chapman & Hall/CRC Textbooks in Computing
Zusatzinfo 5 Tables, color
Sprache englisch
Maße 178 x 254 mm
Gewicht 453 g
Themenwelt Mathematik / Informatik Informatik Programmiersprachen / -werkzeuge
Informatik Theorie / Studium Algorithmen
ISBN-10 0-367-61335-2 / 0367613352
ISBN-13 978-0-367-61335-8 / 9780367613358
Zustand Neuware
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