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.

“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“Havill's broad and applications-driven introduction gives students a strong foundation as they begin to explore our field. Topics that students will study in more depth in later courses are introduced in context along a path of discovery for the fundamentals and breadth of computing. Problem solving paradigms and the structures to implement and test their results are presented as intuitive solutions to real-world problems like DNA sequencing and social network analysis, empowering the reader to understand why programming structures exist and how to use them to solve problems effectively and efficiently. 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“Programming is an essential skill of modern problem solving. But students can gain traction on authentic problems only when they have learned to model, decompose, approximate, and recompose real-world systems into a form suited to computing. 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

• 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 NAMESPACESSUMMARY AND FURTHER DISCOVERY Inside a Computer COMPUTERS ARE DUMB EVERYTHING IS BITSCOMPUTER 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 DNAFIRST STEPS TEXT DOCUMENTSA CONCORDANCEWORD FREQUENCY TRENDSCOMPARING TEXTSTIME COMPLEXITYCOMPUTATIONAL 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 SORTINSERTION SORTEFFICIENT SORTINGTRACTABLE AND INTRACTABLE ALGORITHMSSUMMARY 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

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.

“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“Havill's broad and applications-driven introduction gives students a strong foundation as they begin to explore our field. Topics that students will study in more depth in later courses are introduced in context along a path of discovery for the fundamentals and breadth of computing. Problem solving paradigms and the structures to implement and test their results are presented as intuitive solutions to real-world problems like DNA sequencing and social network analysis, empowering the reader to understand why programming structures exist and how to use them to solve problems effectively and efficiently. 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“Programming is an essential skill of modern problem solving. But students can gain traction on authentic problems only when they have learned to model, decompose, approximate, and recompose real-world systems into a form suited to computing. 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

• 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 NAMESPACESSUMMARY AND FURTHER DISCOVERY Inside a Computer COMPUTERS ARE DUMB EVERYTHING IS BITSCOMPUTER 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 DNAFIRST STEPS TEXT DOCUMENTSA CONCORDANCEWORD FREQUENCY TRENDSCOMPARING TEXTSTIME COMPLEXITYCOMPUTATIONAL 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 SORTINSERTION SORTEFFICIENT SORTINGTRACTABLE AND INTRACTABLE ALGORITHMSSUMMARY 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