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1.

電子ブック

EB
Valérie Issarny, Takeo Kanade, Richard Schantz, Association for Computing Machinery-Digital Library.
出版情報: ACM Digital Library Proceedings , Springer Berlin Heidelberg, 2008
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2.

電子ブック

EB
The 45th Annual Design Automation Conference 2008, Association for Computing Machinery-Digital Library.
出版情報: ACM Digital Library Proceedings , 2008
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3.

電子ブック

EB
Association for Computing Machinery-Digital Library.
出版情報: ACM Digital Library Proceedings , 2008
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4.

電子ブック

EB
J. C. Huang
出版情報: Cambridge University Press Online Books , 2008
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5.

電子ブック

EB
E.-R Olderog, Henning Dierks, Ernst-Rüdiger Olderog
出版情報: Cambridge University Press Online Books , 2008
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目次情報: 続きを見る
Preface
Acknowledgements
List of symbols
Introduction / 1:
What is a real-time system? / 1.1:
System properties / 1.2:
Generalised railroad crossing / 1.3:
Gas burner / 1.4:
Aims of this book / 1.5:
Exercises / 1.6:
Bibliographic remarks / 1.7:
Duration Calculus / 2:
Preview / 2.1:
Syntax and semantics / 2.2:
Specification and correctness proof / 2.3:
Proof rules / 2.4:
Properties and subsets of DC / 2.5:
Decidability results / 3.1:
Implementables / 3.2:
Constraint Diagrams / 3.3:
Timed automata / 3.4:
Networks of timed automata / 4.1:
Reachability is decidable / 4.3:
The model checker UPPAAL / 4.4:
PLC-Automata / 4.5:
Programmable Logic Controllers / 5.1:
Translation into PLC source code / 5.2:
Duration Calculus semantics / 5.4:
Synthesis from DC implementables / 5.5:
Extensions of PLC-Automata / 5.6:
Automatic verification / 5.7:
The approach / 6.1:
Requirements / 6.2:
Specification / 6.3:
Verification / 6.4:
The tool Moby/RT / 6.5:
Summary / 6.6:
Notations / 6.7:
Bibliography
Index
Preface
Acknowledgements
List of symbols
6.

電子ブック

EB
Jonathan Jacky, Colin Campbell, Wolfram Schulte, Margus Veanes
出版情報: Cambridge University Press Online Books , 2008
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目次情報: 続きを見る
Overview / Part I:
Describe, analyze, test / 1:
Why we need model-based testing / 2:
Why we need model-based analysis / 3:
Further reading / 4:
Systems with Finite Models / Part II:
Model programs / 5:
Exploring and analyzing finite models / 6:
Structuring model programs with features and composition / 7:
Testing closed systems / 8:
Systems with Complex States / 9:
Modeling systems with structured state / 10:
Analyzing systems with complex state / 11:
Testing systems with complex state / 12:
Advanced Topics / 13:
Compositional modeling / 14:
Modeling objects / 15:
Reactive systems / 16:
Appendices / 17:
Modeling library reference / A:
Command reference / B:
Glossary / C:
Index / D:
Overview / Part I:
Describe, analyze, test / 1:
Why we need model-based testing / 2:
7.

電子ブック

EB
Peter Brass
出版情報: Cambridge University Press Online Books , 2008
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目次情報: 続きを見る
Preface
Elementary Structures / 1:
Stack / 1.1:
Queue / 1.2:
Double-Ended Queue / 1.3:
Dynamical Allocation of Nodes / 1.4:
Shadow Copies of Array-Based Structures / 1.5:
Search Trees / 2:
Two Models of Search Trees / 2.1:
General Properties and Transformations / 2.2:
Height of a Search Tree / 2.3:
Basic Find, Insert, and Delete / 2.4:
Returning from Leaf to Root / 2.5:
Dealing with Nonunique Keys / 2.6:
Queries for the Keys in an Interval / 2.7:
Building Optimal Search Trees / 2.8:
Converting Trees into Lists / 2.9:
Removing a Tree / 2.10:
Balanced Search Trees / 3:
Height-Balanced Trees / 3.1:
Weight-Balanced Trees / 3.2:
(a, b)- and B-Trees / 3.3:
Red-Black Trees and Trees of Almost Optimal Height / 3.4:
Top-Down Rebalancing for Red-Black Trees / 3.5:
Trees with Constant Update Time at a Known Location / 3.6:
Finger Trees and Level Linking / 3.7:
Trees with Partial Rebuilding: Amortized Analysis / 3.8:
Splay Trees: Adaptive Data Structures / 3.9:
Skip Lists: Randomized Data Structures / 3.10:
Joining and Splitting Balanced Search Trees / 3.11:
Tree Structures for Sets of Intervals / 4:
Interval Trees / 4.1:
Segment Trees / 4.2:
Trees for the Union of Intervals / 4.3:
Trees for Sums of Weighted Intervals / 4.4:
Trees for Interval-Restricted Maximum Sum Queries / 4.5:
Orthogonal Range Trees / 4.6:
Higher-Dimensional Segment Trees / 4.7:
Other Systems of Building Blocks / 4.8:
Range-Counting and the Semigroup Model / 4.9:
kd-Trees and Related Structures / 4.10:
Heaps / 5:
Balanced Search Trees as Heaps / 5.1:
Array-Based Heaps / 5.2:
Heap-Ordered Trees and Half-Ordered Trees / 5.3:
Leftist Heaps / 5.4:
Skew Heaps / 5.5:
Binomial Heaps / 5.6:
Changing Keys in Heaps / 5.7:
Fibonacci Heaps / 5.8:
Heaps of Optimal Complexity / 5.9:
Double-Ended Heap Structures and Multidimensional Heaps / 5.10:
Heap-Related Structures with Constant-Time Updates / 5.11:
Union-Find and Related Structures / 6:
Union-Find: Merging Classes of a Partition / 6.1:
Union-Find with Copies and Dynamic Segment Trees / 6.2:
List Splitting / 6.3:
Problems on Root-Directed Trees / 6.4:
Maintaining a Linear Order / 6.5:
Data Structure Transformations / 7:
Making Structures Dynamic / 7.1:
Making Structures Persistent / 7.2:
Data Structures for Strings / 8:
Tries and Compressed Tries / 8.1:
Dictionaries Allowing Errors in Queries / 8.2:
Suffix Trees / 8.3:
Suffix Arrays / 8.4:
Hash Tables / 9:
Basic Hash Tables and Collision Resolution / 9.1:
Universal Families of Hash Functions / 9.2:
Perfect Hash Functions / 9.3:
Hash Trees / 9.4:
Extendible Hashing / 9.5:
Membership Testers and Bloom Filters / 9.6:
Appendix / 10:
The Pointer Machine and Alternative Computation Models / 10.1:
External Memory Models and Cache-Oblivious Algorithms / 10.2:
Naming of Data Structures / 10.3:
Solving Linear Recurrences / 10.4:
Very Slowly Growing Functions / 10.5:
References / 11:
Author Index
Subject Index
Preface
Elementary Structures / 1:
Stack / 1.1:
8.

電子ブック

EB
Jeff Edmonds
出版情報: Cambridge University Press Online Books , Cambridge University Press, 2008
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目次情報: 続きを見る
Preface
Introduction
Iterative Algorithms and Loop Invariants / Part 1:
Iterative Algorithms: Measures of Progress and Loop Invariants / 1:
A Paradigm Shift: A Sequence of Actions vs. a Sequence of Assertions / 1.1:
The Steps to Develop an Iterative Algorithm / 1.2:
More about the Steps / 1.3:
Different Types of Iterative Algorithms / 1.4:
Typical Errors / 1.5:
Exercises / 1.6:
Examples Using More-of-the-Input Loop Invariants / 2:
Coloring the Plane / 2.1:
Deterministic Finite Automaton / 2.2:
More of the Input vs. More of the Output / 2.3:
Abstract Data Types / 3:
Specifications and Hints at Implementations / 3.1:
Link List Implementation / 3.2:
Merging with a Queue / 3.3:
Parsing with a Stack / 3.4:
Narrowing the Search Space: Binary Search / 4:
Binary Search Trees / 4.1:
Magic Sevens / 4.2:
VLSI Chip Testing / 4.3:
Iterative Sorting Algorithms / 4.4:
Bucket Sort by Hand / 5.1:
Counting Sort (a Stable Sort) / 5.2:
Radix Sort / 5.3:
Radix Counting Sort / 5.4:
Euclid's GCD Algorithm / 6:
The Loop Invariant for Lower Bounds / 7:
Recursion / Part 2:
Abstractions, Techniques, and Theory / 8:
Thinking about Recursion / 8.1:
Looking Forward vs. Backward / 8.2:
With a Little Help from Your Friends / 8.3:
The Towers of Hanoi / 8.4:
Checklist for Recursive Algorithms / 8.5:
The Stack Frame / 8.6:
Proving Correctness with Strong Induction / 8.7:
Some Simple Examples of Recursive Algorithms / 9:
Sorting and Selecting Algorithms / 9.1:
Operations on Integers / 9.2:
Ackermann's Function / 9.3:
Recursion on Trees / 9.4:
Tree Traversals / 10.1:
Simple Examples / 10.2:
Generalizing the Problem Solved / 10.3:
Heap Sort and Priority Queues / 10.4:
Representing Expressions with Trees / 10.5:
Recursive Images / 11:
Drawing a Recursive Image from a Fixed Recursive and a Base Case Image / 11.1:
Randomly Generating a Maze / 11.2:
Parsing with Context-Free Grammars / 12:
Optimization Problems / Part 3:
Definition of Optimization Problems / 13:
Graph Search Algorithms / 14:
A Generic Search Algorithm / 14.1:
Breadth-First Search for Shortest Paths / 14.2:
Dijkstra's Shortest-Weighted-Path Algorithm / 14.3:
Depth-First Search / 14.4:
Recursive Depth-First Search / 14.5:
Linear Ordering of a Partial Order / 14.6:
Exercise / 14.7:
Network Flows and Linear Programming / 15:
A Hill-Climbing Algorithm with a Small Local Maximum / 15.1:
The Primal-Dual Hill-Climbing Method / 15.2:
The Steepest-Ascent Hill-Climbing Algorithm / 15.3:
Linear Programming / 15.4:
Greedy Algorithms / 15.5:
Examples of Greedy Algorithms / 16.1:
Example: The Job/Event Scheduling Problem / 16.2.1:
Example: The Interval Cover Problem / 16.2.2:
Example: The Minimum-Spanning-Tree Problem / 16.2.3:
Recursive Backtracking / 16.3:
Recursive Backtracking Algorithms / 17.1:
The Steps in Developing a Recursive Backtracking / 17.2:
Pruning Branches / 17.3:
Satisfiability / 17.4:
Dynamic Programming Algorithms / 17.5:
Start by Developing a Recursive Backtracking / 18.1:
The Steps in Developing a Dynamic Programming Algorithm / 18.2:
Subtle Points / 18.3:
The Question for the Little Bird / 18.3.1:
Subinstances and Subsolutions / 18.3.2:
The Set of Subinstances / 18.3.3:
Decreasing Time and Space / 18.3.4:
Counting the Number of Solutions / 18.3.5:
The New Code / 18.3.6:
Examples of Dynamic Programs / 19:
The Longest-Common-Subsequence Problem / 19.1:
Dynamic Programs as More-of-the-Input Iterative Loop Invariant Algorithms / 19.2:
A Greedy Dynamic Program: The Weighted Job/Event Scheduling Problem / 19.3:
The Solution Viewed as a Tree: Chains of Matrix Multiplications / 19.4:
Generalizing the Problem Solved: Best AVL Tree / 19.5:
All Pairs Using Matrix Multiplication / 19.6:
Designing Dynamic Programming Algorithms via Reductions / 19.7:
Reductions and NP-Completeness / 20:
Satisfiability Is at Least as Hard as Any Optimization Problem / 20.1:
Steps to Prove NP-Completeness / 20.2:
Example: 3-Coloring Is NP-Complete / 20.3:
An Algorithm for Bipartite Matching Using the Network Flow Algorithm / 20.4:
Randomized Algorithms / 21:
Using Randomness to Hide the Worst Cases / 21.1:
Solutions of Optimization Problems with a Random Structure / 21.2:
Appendix / Part 4:
Existential and Universal Quantifiers / 22:
Time Complexity / 23:
The Time (and Space) Complexity of an Algorithm / 23.1:
The Time Complexity of a Computational Problem / 23.2:
Logarithms and Exponentials / 24:
Asymptotic Growth / 25:
Steps to Classify a Function / 25.1:
More about Asymptotic Notation / 25.2:
Adding-Made-Easy Approximations / 26:
The Technique / 26.1:
Some Proofs for the Adding-Made-Easy Technique / 26.2:
Recurrence Relations / 27:
Some Proofs / 27.1:
A Formal Proof of Correctness / 28:
Exercise Solutions / Part 5:
Conclusion
Index
Preface
Introduction
Iterative Algorithms and Loop Invariants / Part 1:
9.

電子ブック

EB
Wilhelm Schäfer, Association for Computing Machinery-Digital Library.
出版情報: IEEE/IET Electronic Library (IEL) Conference Proceedings , 2008
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10.

電子ブック

EB
The 45th Annual Design Automation Conference 2008, Association for Computing Machinery-Digital Library.
出版情報: IEEE/IET Electronic Library (IEL) Conference Proceedings , 2008
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