Algorithms and data structures the science of computing

The Science of Computing represents the culmination of a project that has been in development for a very long time. In the course of the project, a great many people and organizations have contributed in many ways. While it is impossible to list them all, we do wish to mention some whose contributions have been especially important. The research into the methodology was supported by both the National Science Foundation and the U. S. Department of Education, and we are grateful for their support. During the first several years of the project, Hans Koomen was a co-investigator who played a central role in the developmental work. We received valuable feedback in the form of reviews from many including John Hamer, Peter Henderson, Lew Hitchner, Kris Powers, Orit Hazzan, Mark LeBlanc, Allen Tucker, Tony Ralston, Daniel Hyde, Stuart Hirshfield, Tim Gegg-Harrison, Nicholas Howe, Catherine McGeoch, and Ken Slonneger. G. Michael Schneider and Jim Leisy were also particularly encouraging of our efforts. Homma Farian, Indu Talwar, and Nancy Jones all used drafts of the text in their courses, helping with that crucial first exposure. We held a series of workshops at SUNY Geneseo at which some of the ideas were fleshed out. Faculty from other institutions who attended and contributed their ideas include Elizabeth Adams, Hans-Peter Appelt, Lois Brady, Marcus Brown, John Cross, Nira Herrmann, Margaret I wobi, Margaret Reek, Ethel Schuster, James Slack, and Fengman Zhang. Almost 1500 students served as the front line soldiers—the ones who contributed as the guinea pigs of our efforts—but we especially wish to thank Suzanne Selib, Jim Durbin, Bruce Cowley, Ernie Johnson, Coralie Ashworth, Kevin Kosieracki, Greg Arnold, Steve Batovsky, Wendy Abbott, Lisa Ciferri, Nandini Mehta, Steve Bender, Mary Johansen, Peter Denecke, Jason Kapusta, Michael Stringer, Jesse Smith, Garrett Briggs, Elena Kornienko, and Genevieve Herres, all of whom worked directly with us on stages of the project. Finally, we could not have completed this project without the staff of Charles River Media, especially Stephen Mossberg, David Pallai, and Bryan Davidson.

Preface
Algorithms and Data Structures: The Science of Computing (which we usually refer to simply as The Science of Computing) is about understanding computation. We see it as a distinct departure from previous second-course computer science texts, which emphasize building computations. The Science of Computing develops understanding by coupling algorithm design to mathematical and experimental techniques for modeling and observing algorithms' behavior. Its attention to rigorous scientific experimentation particularly distinguishes it from other computing texts. The Science of Computing introduces students to computer science's three core methods of inquiry: design, mathematical theory, and the scientific method. It introduces these methods early in the curriculum, so that students can use them throughout their studies. The book uses a strongly hands-on approach to demonstrate the importance of, and interactions between, all three methods.

THE TARGET AUDIENCE
The target course for The Science of Computing is the second course in a computer science curriculum (CS 2). For better or worse, that course has become more varied in recent years. The Science of Computing is appropriate for many—but not all—implementations of CS 2.

The Target Student
The Science of Computing is aimed at students who are majoring in, or independently studying, computer science. It is also suitable for students who want to combine a firm background in computer science with another major.

The programming language for examples and exercises in this book is Java. We assume that students have had an introductory programming course using an object-oriented language, although not necessarily Java. The book should also be accessible with just a little extra work to those who started with a procedural language. An appendix helps students whose previous experience is with a language other than Java make the transition to Java.

There is quite a bit of math in The Science of Computing. We teach all of the essential mathematics within the text, assuming only that readers have a good precollege math background. However, readers who have completed one or more college-level math courses, particularly in discrete math, will inevitably have an easier time with the math in this book than readers without such a background.


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Judul : Algorithms and data structures the science of computing
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