Mark allen weiss data structures and algorithm analysis in java

Data Structures and Algorithm Analysis in Java

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. This text is for readers who want to learn good programming and algorithm analysis skills simultaneously so that they can develop such programs with the maximum amount of efficiency. Readers should have some knowledge of intermediate programming, including topics as object-based programming and recursion, and some background in discrete math.

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.

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Об авторе (2012)

Mark Allen Weiss is Professor and Associate Director for the School of Computing and Information Sciences at Florida International University. He is also currently serving as both Director of Undergraduate Studies and Director of Graduate Studies. He received his Bachelor’s Degree in Electrical Engineering from the Cooper Union in 1983, and his Ph.D. in Computer Science from Princeton University in 1987, working under Bob Sedgewick. He has been at FIU since 1987 and was promoted to Professor in 1996. His interests include data structures, algorithms, and education. He is most well-known for his highly-acclaimed Data Structures textbooks, which have been used for a generation by roughly a million students. Professor Weiss is the author of numerous publications in top-rated journals and was recipient of the University’s Excellence in Research Award in 1994. In 1996 at FIU he was the first in the world to teach Data Structures using the Java programming language, which is now the de facto standard. From 1997-2004 he served as a member of the Advanced Placement Computer Science Development Committee, chairing the committee from 2000-2004. The committee designed the curriculum and wrote the AP exams that were taken by 20,000 high school students annually. In addition to his Research Award in 1994, Professor Weiss is also the recipient of the University’s Excellence in Teaching Award in 1999 and the School of Computing and Information Science Excellence in Teaching Award (2005) and Excellence in Service Award (2007).

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Библиографические данные

Название Data Structures and Algorithm Analysis in Java
Автор Mark Allen Weiss
Издание: 3, исправленное
Издатель Pearson, 2012
ISBN 0132576279, 9780132576277
Количество страниц Всего страниц: 614
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Data structures and algorithm analysis in Java

Algorithm analysis — Lists, stacks, and queues — Trees — Hashing — Priority queues (Heaps) — Sorting — The Disjoint Set class — Graph algorithms — Algorithm design techniques — Amortized analysis — Advanced data structures implementation

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Data structures & algorithm analysis in Java

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Data Structures and Algorithm Analysis in Java 3rd Edition Weiss Solutions Manual [3 ed.] 0132576279, 9780132576277

Data Structures and Algorithm Analysis in Java [3 ed.] 9780132576277, 0132576279, 2011035536

The general way to do this is to write a procedure with heading void processFile( String fileName ); which opens fileName, does whatever processing is needed, and then closes it. If a line of the form #include SomeFile is detected, then the call processFile( SomeFile ); is made recursively. Self-referential includes can be detected by keeping a list of files for which a call to processFile has not yet terminated, and checking this list before making a new call to processFile.

public static int ones( int n )

(a) A. (b) B. (c) The information given is not sufficient to determine an answer. We have only worst-case bounds. (d) Yes.

(a) Recursion is unnecessary if there are two or fewer elements. (b) One way to do this is to note that if the first N – 1 elements have a majority, then the last element cannot change this. Otherwise, the last element could be a majority. Thus if N is odd, ignore the last element. Run the algorithm as before. If no majority element emerges, then return the Nth element as a candidate. (c) The running time is O(N), and satisfies T(N) = T(N/2) + O(N). (d) One copy of the original needs to be saved. After this, the B array, and indeed the recursion, can be avoided by placing each Bi in the A array. The difference is that the original recursive strategy implies that O(log N) arrays are used; this guarantees only two copies.

Start from the top-right corner. With a comparison, either a match is found, we go left, or we go down. Therefore, the number of comparisons is linear.

(a, c) Find the two largest numbers in the array. (b, d) Similar solutions; (b) is described here. The maximum difference is at least zero (i  j), so that can be the initial value of the answer to beat. At any point in the algorithm, we have the current value j, and the current low point i. If a[j] – a[i] is larger than the current best, update the best difference. If a[j] is less than

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a[i], reset the current low point to i. Start with i at index 0, j at index 0. j just scans the array, so the running time is O(N). 2.29

Otherwise, we could perform operations in parallel by cleverly encoding several integers into one. For instance, if A = 001, B = 101, C = 111, D = 100, we could add A and B at the same time as C and D by adding 00A00C + 00B00D. We could extend this to add N pairs of numbers at once in unit cost.

No. If low = 1, high = 2, then mid = 1, and the recursive call does not make progress.

No. As in Exercise 2.31, no progress is made.

See my textbook Data Structures and Problem Solving using Java for an explanation.

Lists, Stacks, and Queues 3.1

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Address: 1918 St.Regis, Dorval, Quebec, H9P 1H6, Canada.

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Shu ju jie gou yu suan fa fen xi : Java yu yan miao shu = Data structures and algorithm analysis in Java

Publication date 2009 Topics JAVA yu yan — Shu ju jie gou — Suan fa fen xi, JAVA yu yan, Shu ju jie gou, Suan fa fen xi Publisher Beijing : Ji xie gong ye chu ban she Collection inlibrary; printdisabled; popularchinesebooks; internetarchivebooks; china Digitizing sponsor Kahle/Austin Foundation Contributor Internet Archive Language Chinese Title (alternate script) 数据结构与算法分析 : Java语言描述 = Data structures and algorithm analysis in Java Author (alternate script) 韦斯

Ben shu tao lun le shu ju jie gou he suan fa fen xi, Hai tao lun le gao ji shu ju jie gou ji qi shi xian, Bing zai cheng xu dai ma zhong chong fen ti xian le Java5.0 de xin te xing

Bing lie ti ming:Data structures and algorithm analysis in Java

Qi ta ti ming:Java yu yan miao shu

Mei guo pei sheng jiao yu chu ban ji tuan shou quan chu ban

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