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data structures midterm exam: Basic Data Structures and Program Statements Xingni Zhou, Qiguang Miao, Lei Feng, 2020-09-21 This book covers C-Programming focussing on its practical side. Volume 1 deals mainly with basic data structures, algorithms and program statements. An extensive use of figures and examples help to give a clear description of concepts help the reader to gain a systematic understanding of the language. |
data structures midterm exam: Data Structures and Algorithms in Java Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, 2014-01-28 The design and analysis of efficient data structures has long been recognized as a key component of the Computer Science curriculum. Goodrich, Tomassia and Goldwasser's approach to this classic topic is based on the object-oriented paradigm as the framework of choice for the design of data structures. For each ADT presented in the text, the authors provide an associated Java interface. Concrete data structures realizing the ADTs are provided as Java classes implementing the interfaces. The Java code implementing fundamental data structures in this book is organized in a single Java package, net.datastructures. This package forms a coherent library of data structures and algorithms in Java specifically designed for educational purposes in a way that is complimentary with the Java Collections Framework. |
data structures midterm exam: The Algorithm Design Manual Steven S Skiena, 2009-04-05 This newly expanded and updated second edition of the best-selling classic continues to take the mystery out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW war stories relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java |
data structures midterm exam: Data Structures and Algorithms in Python Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, 2013-06-17 Based on the authors' market leading data structures books in Java and C++, this book offers a comprehensive, definitive introduction to data structures in Python by authoritative authors. Data Structures and Algorithms in Python is the first authoritative object-oriented book available for Python data structures. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++. Begins by discussing Python's conceptually simple syntax, which allows for a greater focus on concepts. Employs a consistent object-oriented viewpoint throughout the text. Presents each data structure using ADTs and their respective implementations and introduces important design patterns as a means to organize those implementations into classes, methods, and objects. Provides a thorough discussion on the analysis and design of fundamental data structures. Includes many helpful Python code examples, with source code provided on the website. Uses illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Provides hundreds of exercises that promote creativity, help readers learn how to think like programmers, and reinforce important concepts. Contains many Python-code and pseudo-code fragments, and hundreds of exercises, which are divided into roughly 40% reinforcement exercises, 40% creativity exercises, and 20% programming projects. |
data structures midterm exam: Open Data Structures Pat Morin, 2013 Introduction -- Array-based lists -- Linked lists -- Skiplists -- Hash tables -- Binary trees -- Random binary search trees -- Scapegoat trees -- Red-black trees -- Heaps -- Sorting algorithms -- Graphs -- Data structures for integers -- External memory searching. |
data structures midterm exam: Data Structures and Algorithm Analysis in C++ Weiss, Weiss Mark Allen, 2007-09 The C++ language is brought up-to-date and simplified, and the Standard Template Library is now fully incorporated throughout the text. Data Structures and Algorithm Analysis in C++ is logically organized to cover advanced data structures topics from binary heaps to sorting to NP-completeness. Figures and examples illustrating successive stages of algorithms contribute to Weiss' careful, rigorous and in-depth analysis of each type of algorithm. |
data structures midterm exam: Data structures based on non-linear relations and data processing methods Xingni Zhou, Zhiyuan Ren, Yanzhuo Ma, Kai Fan, Xiang Ji, 2020-06-08 The systematic description starts with basic theory and applications of different kinds of data structures, including storage structures and models. It also explores on data processing methods such as sorting, index and search technologies. Due to its numerous exercises the book is a helpful reference for graduate students, lecturers. |
data structures midterm exam: Data Structures Using Java Duncan A. Buell, 2013 Data Structures & Theory of Computation |
data structures midterm exam: Pascal Plus Data Structures, Algorithms, and Advanced Programming Nell B. Dale, Susan C. Lilly, 1995 |
data structures midterm exam: Composite Data Structures and Modularization Xingni Zhou, Qiguang Miao, Lei Feng, 2020-10-26 This book covers C-Programming focussing on its practical side. Volume 2 deals mainly with composite data structures and their composition. An extensive use of figures and examples help to give a clear description of concepts and help the reader to gain a systematic understanding of the programming language. |
data structures midterm exam: Introduction to Algorithms, third edition Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, 2009-07-31 The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide. |
data structures midterm exam: The Design and Analysis of Algorithms Dexter C. Kozen, 2012-12-06 These are my lecture notes from CS681: Design and Analysis of Algo rithms, a one-semester graduate course I taught at Cornell for three consec utive fall semesters from '88 to '90. The course serves a dual purpose: to cover core material in algorithms for graduate students in computer science preparing for their PhD qualifying exams, and to introduce theory students to some advanced topics in the design and analysis of algorithms. The material is thus a mixture of core and advanced topics. At first I meant these notes to supplement and not supplant a textbook, but over the three years they gradually took on a life of their own. In addition to the notes, I depended heavily on the texts • A. V. Aho, J. E. Hopcroft, and J. D. Ullman, The Design and Analysis of Computer Algorithms. Addison-Wesley, 1975. • M. R. Garey and D. S. Johnson, Computers and Intractibility: A Guide to the Theory of NP-Completeness. w. H. Freeman, 1979. • R. E. Tarjan, Data Structures and Network Algorithms. SIAM Regional Conference Series in Applied Mathematics 44, 1983. and still recommend them as excellent references. |
data structures midterm exam: C++ Plus Data Structures Nell B. Dale, 2003 Computer Science |
data structures midterm exam: Data Structures and Algorithms in Java Adam Drozdek, 2004-09-24 Using the Java programming language, author Adam Drozdek highlights three important aspects of data structures and algorithms. First, the book places special emphasis on the connection between data structures and their algorithms, including an analysis of the algorithms’ complexity. Second, the book presents data structures in the context of object-oriented program design, stressing the principle of information hiding in its treatment of encapsulation and decomposition. Finally, the book closely examines data structure implementation. Overall, this practical and theoretical book prepares students with a solid foundation in data structures for future courses and work in design implementation, testing, or maintenance of virtually any software system. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version. |
data structures midterm exam: Data Structures and Algorithms Kurt Mehlhorn, 1984 Band 3. |
data structures midterm exam: Text Algorithms Maxime Crochemore, Wojciech Rytter, 1994 This much-needed book on the design of algorithms and data structures for text processing emphasizes both theoretical foundations and practical applications. It is intended to serve both as a textbook for courses on algorithm design, especially those related to text processing, and as a reference for computer science professionals. The work takes a unique approach, one that goes more deeply into its topic than other more general books. It contains both classical algorithms and recent results of research on the subject. The book is the first text to contain a collection of a wide range of text algorithms, many of them quite new and appearing here for the first time. Other algorithms, while known by reputation, have never been published in the journal literature. Two such important algorithms are those of Karp, Miller and Rosenberg, and that of Weiner. Here they are presented together for the fist time. The core of the book is the material on suffix trees and subword graphs, applications of these data structures, new approaches to time-space optimal string-matching, and text compression. Also covered are basic parallel algorithms for text problems. Applications of all these algorithms are given for problems involving data retrieval systems, treatment of natural languages, investigation of genomes, data compression software, and text processing tools. From the theoretical point of view. the book is a goldmine of paradigms for the development of efficient algorithms, providing the necessary foundation to creating practical software dealing with sequences. A crucial point in the authors' approach is the development of a methodology for presenting text algorithms so they can be fully understood. Throughout, the book emphasizes the efficiency of algorithms, holding that the essence of their usefulness depends on it. This is especially important since the algorithms described here will find application in Big Science areas like molecular sequence analysis where the explosive growth of data has caused problems for the current generation of software. Finally, with its development of theoretical background, the book can be considered as a mathematical foundation for the analysis and production of text processing algorithms. |
data structures midterm exam: Data Structures Using C++ D. S. Malik, 2010 The latest book from Cengage Learning on Data Structures Using C++, International Edition |
data structures midterm exam: Handbook of Research on Modern Systems Analysis and Design Technologies and Applications Syed, Mahbubur Rahman, Syed, Sharifun Nessa, 2008-07-31 This book provides a compendium of terms, definitions, and explanations of concepts in various areas of systems and design, as well as a vast collection of cutting-edge research articles from the field's leading experts--Provided by publisher. |
data structures midterm exam: Objects, Abstraction, Data Structures and Design Elliot B. Koffman, Paul A. T. Wolfgang, 2005-10-20 Koffman and Wolfgang introduce data structures in the context of C++ programming. They embed the design and implementation of data structures into the practice of sound software design principles that are introduced early and reinforced by 20 case studies. Data structures are introduced in the C++ STL format whenever possible. Each new data structure is introduced by describing its interface in the STL. Next, one or two simpler applications are discussed then the data structure is implemented following the interface previously introduced. Finally, additional advanced applications are covered in the case studies, and the cases use the STL. In the implementation of each data structure, the authors encourage students to perform a thorough analysis of the design approach and expected performance before actually undertaking detailed design and implementation. Students gain an understanding of why different data structures are needed, the applications they are suited for, and the advantages and disadvantages of their possible implementations. Case studies follow a five-step process (problem specification, analysis, design, implementation, and testing) that has been adapted to object-oriented programming. Students are encouraged to think critically about the five-step process and use it in their problem solutions. Several problems have extensive discussions of testing and include methods that automate the testing process. Some cases are revisited in later chapters and new solutions are provided that use different data structures. The text assumes a first course in programming and is designed for Data Structures or the second course in programming, especially those courses that include coverage of OO design and algorithms. A C++ primer is provided for students who have taken a course in another programming language or for those who need a review in C++. Finally, more advanced coverage of C++ is found in an appendix. Course Hierarchy: Course is the second course in the CS curriculum Required of CS majors Course names include Data Structures and Data Structures & Algorithms |
data structures midterm exam: Program Arcade Games Paul Craven, 2015-12-31 Learn and use Python and PyGame to design and build cool arcade games. In Program Arcade Games: With Python and PyGame, Second Edition, Dr. Paul Vincent Craven teaches you how to create fun and simple quiz games; integrate and start using graphics; animate graphics; integrate and use game controllers; add sound and bit-mapped graphics; and build grid-based games. After reading and using this book, you'll be able to learn to program and build simple arcade game applications using one of today's most popular programming languages, Python. You can even deploy onto Steam and other Linux-based game systems as well as Android, one of today's most popular mobile and tablet platforms. You'll learn: How to create quiz games How to integrate and start using graphics How to animate graphics How to integrate and use game controllers How to add sound and bit-mapped graphics How to build grid-based games Audience“div>This book assumes no prior programming knowledge. |
data structures midterm exam: Algorithm Design Michael T. Goodrich, Roberto Tamassia, 2001-10-15 Michael Goodrich and Roberto Tamassia, authors of the successful, Data Structures and Algorithms in Java, 2/e, have written Algorithm Engineering, a text designed to provide a comprehensive introduction to the design, implementation and analysis of computer algorithms and data structures from a modern perspective. This book offers theoretical analysis techniques as well as algorithmic design patterns and experimental methods for the engineering of algorithms. Market: Computer Scientists; Programmers. |
data structures midterm exam: Data Structures & Algorithms Interview Questions You'll Most Likely Be Asked Vibrant Publishers, 2016-12-14 Features: 200 Data Structures & Algorithms Interview Questions; 77 HR Interview Questions; Real-life scenario based questions; Strategies to respond to interview questions; 2 Aptitude Tests. The book is a perfect companion to stand ahead above the rest in todays competitive job market. Rather than going through comprehensive, textbook-sized reference guides, this book includes only the information required immediately for job search to build an IT career. This book puts the interviewee in the driver's seat and helps them steer their way to impress the interviewer. |
data structures midterm exam: Pascal Plus Data Structures, Algorithms and Advanced Programming Dale/Lilly, Nell B. Dale, Susan C. Lilly, 1991 |
data structures midterm exam: Data Abstraction and Problem Solving with Java: Walls and Mirrors Janet Prichard, Frank M. Carrano, 2014-09-18 This edition of Data Abstraction and Problem Solving with Java: Walls and Mirrors employs the analogies of Walls (data abstraction) and Mirrors (recursion) to teach Java programming design solutions, in a way that beginning students find accessible. The book has a student-friendly pedagogical approach that carefully accounts for the strengths and weaknesses of the Java language. With this book, students will gain a solid foundation in data abstraction, object-oriented programming, and other problem-solving techniques. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed. |
data structures midterm exam: Data Structures And Algorithms Shi-kuo Chang, 2003-09-29 This is an excellent, up-to-date and easy-to-use text on data structures and algorithms that is intended for undergraduates in computer science and information science. The thirteen chapters, written by an international group of experienced teachers, cover the fundamental concepts of algorithms and most of the important data structures as well as the concept of interface design. The book contains many examples and diagrams. Whenever appropriate, program codes are included to facilitate learning.This book is supported by an international group of authors who are experts on data structures and algorithms, through its website at www.cs.pitt.edu/~jung/GrowingBook/, so that both teachers and students can benefit from their expertise. |
data structures midterm exam: Computational Topology for Data Analysis Tamal Krishna Dey, Yusu Wang, 2022-03-10 Topological data analysis (TDA) has emerged recently as a viable tool for analyzing complex data, and the area has grown substantially both in its methodologies and applicability. Providing a computational and algorithmic foundation for techniques in TDA, this comprehensive, self-contained text introduces students and researchers in mathematics and computer science to the current state of the field. The book features a description of mathematical objects and constructs behind recent advances, the algorithms involved, computational considerations, as well as examples of topological structures or ideas that can be used in applications. It provides a thorough treatment of persistent homology together with various extensions – like zigzag persistence and multiparameter persistence – and their applications to different types of data, like point clouds, triangulations, or graph data. Other important topics covered include discrete Morse theory, the Mapper structure, optimal generating cycles, as well as recent advances in embedding TDA within machine learning frameworks. |
data structures midterm exam: Algorithm Design and Applications Michael T. Goodrich, Roberto Tamassia, 2014-11-03 ALGORITHM DESIGN and APPLICATIONS “This is a wonderful book, covering both classical and contemporary topics in algorithms. I look forward to trying it out in my algorithms class. I especially like the diversity in topics and difficulty of the problems.” ROBERT TARJAN, PRINCETON UNIVERSITY “The clarity of explanation is excellent. I like the inclusion of the three types of exercises very much.” MING-YANG KAO, NORTHWESTERN UNIVERSITY “Goodrich and Tamassia have designed a book that is both remarkably comprehensive in its coverage and innovative in its approach. Their emphasis on motivation and applications, throughout the text as well as in the many exercises, provides a book well-designed for the boom in students from all areas of study who want to learn about computing. The book contains more than one could hope to cover in a semester course, giving instructors a great deal of flexibility and students a reference that they will turn to well after their class is over.” MICHAEL MITZENMACHER, HARVARD UNIVERSITY “I highly recommend this accessible roadmap to the world of algorithm design. The authors provide motivating examples of problems faced in the real world and guide the reader to develop workable solutions, with a number of challenging exercises to promote deeper understanding.” JEFFREY S. VITTER, UNIVERSITY OF KANSAS DidYouKnow? This book is available as a Wiley E-Text. The Wiley E-Text is a complete digital version of the text that makes time spent studying more efficient. Course materials can be accessed on a desktop, laptop, or mobile device—so that learning can take place anytime, anywhere. A more affordable alternative to traditional print, the Wiley E-Text creates a flexible user experience: Access on-the-go Search across content Highlight and take notes Save money! The Wiley E-Text can be purchased in the following ways: Via your campus bookstore: Wiley E-Text: Powered by VitalSource® ISBN 9781119028796 *Instructors: This ISBN is needed when placing an order. Directly from: www.wiley.com/college/goodrich |
data structures midterm exam: Algorithms Robert Sedgewick, 1988 Software -- Programming Techniques. |
data structures midterm exam: Data Structures and Algorithm Analysis in Java Mark Allen Weiss, 2014-09-24 Data Structures and Algorithm Analysis in Java is an advanced algorithms book that fits between traditional CS2 and Algorithms Analysis courses. In the old ACM Curriculum Guidelines, this course was known as CS7. It is also suitable for a first-year graduate course in algorithm analysis As the speed and power of computers increases, so does the need for effective programming and algorithm analysis. By approaching these skills in tandem, Mark Allen Weiss teaches readers to develop well-constructed, maximally efficient programs in Java. Weiss clearly explains topics from binary heaps to sorting to NP-completeness, and dedicates a full chapter to amortized analysis and advanced data structures and their implementation. Figures and examples illustrating successive stages of algorithms contribute to Weiss’ careful, rigorous and in-depth analysis of each type of algorithm. A logical organization of topics and full access to source code complement the text’s coverage. |
data structures midterm exam: An Introduction to Bioinformatics Algorithms Neil C. Jones, Pavel A. Pevzner, 2004-08-06 An introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics. This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website. |
data structures midterm exam: Object-Oriented Data Structures Using Java Nell Dale, Daniel Joyce, Chip Weems, 2012 Continuing the success of the popular second edition, the updated and revised Object-Oriented Data Structures Using Java, Third Edition is sure to be an essential resource for students learning data structures using the Java programming language. It presents traditional data structures and object-oriented topics with an emphasis on problem-solving, theory, and software engineering principles. Beginning early and continuing throughout the text, the authors introduce and expand upon the use of many Java features including packages, interfaces, abstract classes, inheritance, and exceptions. Numerous case studies provide readers with real-world examples and demonstrate possible solutions to interesting problems. The authors' lucid writing style guides readers through the rigor of standard data structures and presents essential concepts from logical, applications, and implementation levels. Key concepts throughout the Third Edition have been clarified to increase student comprehension and retention, and end-of-chapter exercises have been updated and modified. New and Key Features to the Third Edition: -Includes the use of generics throughout the text, providing the dual benefits of allowing for a type safe use of data structures plus exposing students to modern approaches. -This text is among the first data structures textbooks to address the topic of concurrency and synchonization, which are growing in the importance as computer systems move to using more cores and threads to obtain additional performance with each new generation. Concurrency and synchonization are introduced in the new Section 5.7, where it begins with the basics of Java threads. -Provides numerous case studies and examples of the problem solving process. Each case study includes problem description, an analysis of the problem input and required output, and a discussion of the appropriate data structures to use. -Expanded chapter exercises allow you as the instructor to reinforce topics for your students using both theoretical and practical questions. -Chapters conclude with a chapter summary that highlights the most important topics of the chapter and ties together related topics. |
data structures midterm exam: Data Abstraction and Problem Solving with C++ Frank M. Carrano, Paul Helman, Robert Veroff, 1998 Focusing on data abstraction and data structures, the second edition of this very successful book continues to emphasize the needs of both the instructor and the student. The book illustrates the role of classes and abstract data types (ADTs) in the problem-solving process as the foundation for an object-oriented approach. Throughout the next, the distinction between specification and implementation is continually stressed. The text covers major applications of ADTs, such as searching a flight map and performing an event-driven simulation. It also offers early, extensive coverage of recursion and uses this technique in many examples and exercises. Overall, the lucid writing style, widespread use of examples, and flexible coverage of material have helped make this a leading book in the field. --Book Jacket. |
data structures midterm exam: The Java Programming Language Ken Arnold, James Gosling, David Holmes, 2000 Restructured to deliver in-depth coverage of Java's critical new features, this guide contains code examples to help developers make the most of new Java features. It offers a creator's eye view of the rationale behind Java's design, and its latest enhancements, all designed to help developers make the most of Java's power, portability, and flexibility. |
data structures midterm exam: Head First Java Kathy Sierra, Bert Bates, 2005-02-09 Learning a complex new language is no easy task especially when it s an object-oriented computer programming language like Java. You might think the problem is your brain. It seems to have a mind of its own, a mind that doesn't always want to take in the dry, technical stuff you're forced to study. The fact is your brain craves novelty. It's constantly searching, scanning, waiting for something unusual to happen. After all, that's the way it was built to help you stay alive. It takes all the routine, ordinary, dull stuff and filters it to the background so it won't interfere with your brain's real work--recording things that matter. How does your brain know what matters? It's like the creators of the Head First approach say, suppose you're out for a hike and a tiger jumps in front of you, what happens in your brain? Neurons fire. Emotions crank up. Chemicals surge. That's how your brain knows. And that's how your brain will learn Java. Head First Java combines puzzles, strong visuals, mysteries, and soul-searching interviews with famous Java objects to engage you in many different ways. It's fast, it's fun, and it's effective. And, despite its playful appearance, Head First Java is serious stuff: a complete introduction to object-oriented programming and Java. You'll learn everything from the fundamentals to advanced topics, including threads, network sockets, and distributed programming with RMI. And the new. second edition focuses on Java 5.0, the latest version of the Java language and development platform. Because Java 5.0 is a major update to the platform, with deep, code-level changes, even more careful study and implementation is required. So learning the Head First way is more important than ever. If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. You'll see why people say it's unlike any other Java book you've ever read. By exploiting how your brain works, Head First Java compresses the time it takes to learn and retain--complex information. Its unique approach not only shows you what you need to know about Java syntax, it teaches you to think like a Java programmer. If you want to be bored, buy some other book. But if you want to understand Java, this book's for you. |
data structures midterm exam: Problems on Algorithms Ian Parberry, 1995 With approximately 600 problems and 35 worked examples, this supplement provides a collection of practical problems on the design, analysis and verification of algorithms. The book focuses on the important areas of algorithm design and analysis: background material; algorithm design techniques; advanced data structures and NP-completeness; and miscellaneous problems. Algorithms are expressed in Pascal-like pseudocode supported by figures, diagrams, hints, solutions, and comments. |
data structures midterm exam: Data Structures and Algorithm Analysis in C Mark Allen Weiss, 1997 In this second edition of his best-selling book, Data Structures and Algorithm Analysis in C, Mark Allen Weiss, continues to refine and enhance his innovative approach to algorithms and data structures. Using a C implementation, he highlights conceptual topics, focusing on ADTs and the analysis of algorithms for efficiency as well as performance and running time. Dr Weiss also distinguishes Data Structures and Algorithm Analysis in C with the extensive use of figures and examples showing the successive stages of an algorithm, his engaging writing style, and a logical organization of topics. greedy algorithms, divide and conquer algorithms, dynamic programming, randomized algorithms, and backtracking * Presents current topics and newer data structures such as Fibonacci heaps, skew heaps, binomial queues, skip lists, and splay trees * Contains a chapter on amortized analysis that examines the advanced data structures presented earlier in the book * Provides a new chapter on advanced data structures and their implementation covering red black trees, top down splay trees, treaps, k-d trees, pairing heaps, and more * Incorporates new results on the average case analysis of heapsort * Offers source code from example programs via anonymous FTP 0201498405B04062001 |
data structures midterm exam: Anatomy and Physiology J. Gordon Betts, Peter DeSaix, Jody E. Johnson, Oksana Korol, Dean H. Kruse, Brandon Poe, James A. Wise, Mark Womble, Kelly A. Young, 2013-04-25 |
data structures midterm exam: Graph Theory Ralucca Gera, Teresa W. Haynes, Stephen T. Hedetniemi, 2018-10-26 This second volume in a two-volume series provides an extensive collection of conjectures and open problems in graph theory. It is designed for both graduate students and established researchers in discrete mathematics who are searching for research ideas and references. Each chapter provides more than a simple collection of results on a particular topic; it captures the reader’s interest with techniques that worked and failed in attempting to solve particular conjectures. The history and origins of specific conjectures and the methods of researching them are also included throughout this volume. Students and researchers can discover how the conjectures have evolved and the various approaches that have been used in an attempt to solve them. An annotated glossary of nearly 300 graph theory parameters, 70 conjectures, and over 600 references is also included in this volume. This glossary provides an understanding of parameters beyond their definitions and enables readers to discover new ideas and new definitions in graph theory. The editors were inspired to create this series of volumes by the popular and well-attended special sessions entitled “My Favorite Graph Theory Conjectures,” which they organized at past AMS meetings. These sessions were held at the winter AMS/MAA Joint Meeting in Boston, January 2012, the SIAM Conference on Discrete Mathematics in Halifax in June 2012, as well as the winter AMS/MAA Joint Meeting in Baltimore in January 2014, at which many of the best-known graph theorists spoke. In an effort to aid in the creation and dissemination of conjectures and open problems, which is crucial to the growth and development of this field, the editors invited these speakers, as well as other experts in graph theory, to contribute to this series. |
data structures midterm exam: Data Structures, Algorithms, and Applications in C++ Sartaj Sahni, 2005 |
data structures midterm exam: Data Structures and Problem Solving Using Java Mark Allen Weiss, 1998 This text uses Java to teach data structures and algorithms from the perspective of abstract thinking and problem solving. |
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3 Stack s = new Stack(); String word = "carpets"; int i = 0; while (i < word.length()) { s.push(word.charAt(i)); i++; …