Analysis of AlgorithmsJones & Bartlett Learning, 2008 - 451 lappuses Updated to follow the recommendations put forth by the ACM/SIGCSE 2001 task force, Analysis of Algorithms raises awareness of the effects that algorithms have on the efficiency of a program and develops the necessary skills to analyze general algorithms used in programs. The text presents the material with the expectation that it can be used with active and cooperative learning methodology, based on the premise that students learn more effectively and retain more information longer when they are active participants in the learning process. To accomplish this, the chapters are clear and complete to encourage students to prepare by reading before class, and the text is filled with exciting examples and exercises that look at the efficiency of various algorithms to solve a problem. The author is well known for workshops that he presents on the active learning model. He has written an instructor's manual that helps instructors understand how to present the material in an active way. |
No grāmatas satura
1.–5. rezultāts no 31.
xiv. lappuse
... Context - Free Languages 186 Nondeterministic Pushdown Automata 186 Exercises 187 184 6.6 Context - Free Grammars 187 6.6.1 Context - Free Grammar Abilities 6.6.2 Designing Context - Free Grammars 188 188 Converting a Context - Free ...
... Context - Free Languages 186 Nondeterministic Pushdown Automata 186 Exercises 187 184 6.6 Context - Free Grammars 187 6.6.1 Context - Free Grammar Abilities 6.6.2 Designing Context - Free Grammars 188 188 Converting a Context - Free ...
147. lappuse
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148. lappuse
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186. lappuse
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Saturs
Analysis Basics | 1 |
Recursive Algorithms | 29 |
Searching and Selection Algorithms | 59 |
Sorting Algorithms | 77 |
Numeric Algorithms | 131 |
Formal Language Algorithms | 147 |
Matching Algorithms | 211 |
Graph Algorithms | 231 |
Limits of Computation | 303 |
Other Algorithmic Techniques | 355 |
Pseudorandom Number Table | 399 |
Pseudorandom Number Generation | 403 |
Results of Chapter Study Suggestions | 409 |
References | 429 |
435 | |
Parallel Algorithms | 267 |
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Analysis of Algorithms: An Active Learning Approach Jeffrey J. McConnell Ierobežota priekšskatīšana - 2001 |
Bieži izmantoti vārdi un frāzes
accepting adjacency matrix analysis answer automata backpack biconnected components bubble sort calculate chapter characters class NP complexity consider convex hull create determine deterministic finite automaton edge element encoding end if end equation example EXERCISES FIGURE FORMAL LANGUAGE ALGORITHMS gives graph heap increment insertion sort largest value look loop match matrix multiplication means merge method minimum spanning tree move node nondeterministic finite nondeterministic finite automaton nonterminal symbols number of comparisons operations optimal PARALLEL ALGORITHMS parse tree pass pattern permutations pivot points polynomial possible problem processors pushdown automaton Quicksort read-write head recurrence relation recursive algorithm result rithm rules Section sequential Shellsort shortest path smaller smallest solution solve sorting algorithm stack step subprogram subset substring swap tape target terminal symbols textLoc tion traversal Turing machine word worst write