Algorithms and Theory of Computation Handbook 2 Volume Set Chapman and Hall CRC Applied Algorithms and Data Structures series 2nd Edition by Mikhail Atallah, Marina Blanton ISBN 1584888180 9781584888185

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Product details:
ISBN 10: 1584888180
ISBN 13: 9781584888185
Author: Mikhail Atallah, Marina Blanton

Algorithms and Theory of Computation Handbook, Second Edition provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems.

New to the Second EditionAlong with updating and revising many of the existing chapters, this second edition contains more than 20 new chapters. This edition now covers external memory, parameterized, self-stabilizing, and pricing algorithms as well as the theories of algorithmic coding, privacy and anonymity, databases, computational games, and communication networks. It also discusses computational topology, computational number theory, natural language processing, and grid computing and explores applications in intensity-modulated radiation therapy, voting, DNA research, systems biology, and financial derivatives.

This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.

Algorithms and Theory of Computation Handbook 2 Volume Set Chapman and Hall CRC Applied Algorithms and Data Structures series 2nd Edition Table of contents:

Volume 1: Algorithms

Preface

• Overview of the Handbook
• Audience and Scope
• How to Use This Handbook

Chapter 1: Fundamentals of Algorithms

• Introduction to Algorithms
• Time and Space Complexity Analysis
• Asymptotic Notation (Big-O, Big-Ω, Big-Θ)
• Recurrence Relations
• Algorithm Design Paradigms

Chapter 2: Divide-and-Conquer Algorithms

• Overview of Divide-and-Conquer Strategy
• Merge Sort and Quick Sort
• Strassen’s Matrix Multiplication Algorithm
• Binary Search
• Closest Pair of Points

Chapter 3: Dynamic Programming

• Introduction to Dynamic Programming
• The Knapsack Problem
• Longest Common Subsequence and Substring
• Matrix Chain Multiplication
• Optimal Binary Search Tree

Chapter 4: Greedy Algorithms

• Introduction to Greedy Strategy
• Activity Selection Problem
• Huffman Coding
• Minimum Spanning Trees: Kruskal’s and Prim’s Algorithms
• Fractional Knapsack Problem

Chapter 5: Network Flow and Matching Algorithms

• Network Flow Models
• Ford-Fulkerson Algorithm and Max-Flow Min-Cut Theorem
• Bipartite Matching
• Push-Relabel Algorithm for Maximum Flow
• Applications of Network Flow Algorithms

Chapter 6: NP-Completeness and Computational Intractability

• Introduction to NP-Completeness
• P vs NP Problem
• NP-Hard and NP-Complete Problems
• Reductions and Completeness
• Approximation Algorithms for NP-Hard Problems

Chapter 7: Graph Algorithms

• Graph Representations (Adjacency List, Matrix, etc.)
• Depth-First Search and Breadth-First Search
• Topological Sorting
• Shortest Path Algorithms: Dijkstra’s and Bellman-Ford
• Network Flow and Graph Cut Problems

Chapter 8: Parallel Algorithms

• Introduction to Parallel Computation
• Parallel Algorithms for Sorting
• Parallel Graph Algorithms
• MapReduce Framework
• Scalability and Efficiency in Parallel Algorithms

Chapter 9: Randomized Algorithms

• Introduction to Randomized Algorithms
• Randomized QuickSort and Hashing
• Monte Carlo and Las Vegas Algorithms
• Applications in Approximation and Counting
• Probabilistic Analysis and Random Walks

Volume 2: Theory of Computation

Preface

• Overview of Computation Theory
• Scope and Approach

Chapter 1: Formal Languages and Automata

• Introduction to Formal Languages
• Finite Automata: Deterministic and Non-Deterministic
• Regular Expressions and Regular Languages
• Pumping Lemma for Regular Languages
• Context-Free Languages and Pushdown Automata

Chapter 2: Computability Theory

• Turing Machines: Definition and Variants
• Halting Problem and Undecidability
• Decidability and Recognizability
• Reducibility and the Recursion Theorem
• Church-Turing Thesis

Chapter 3: Complexity Theory

• P, NP, and NP-Complete Problems
• The Polynomial Hierarchy
• PSPACE and EXPTIME
• Time and Space Complexity Classes
• Randomized Complexity Classes

Chapter 4: Logic and Proofs

• Propositional Logic and Predicate Logic
• Logical Calculus and Proof Techniques
• Formal Languages and Logic
• Proofs of Correctness for Algorithms
• Inductive and Recursive Proofs

Chapter 5: Advanced Computability and Complexity

• Interactive Proofs and Cryptographic Protocols
• Complexity of Approximation
• Parallel Computation and Complexity Classes
• Quantum Computing and Complexity
• Advanced Topics in Computation Theory

Chapter 6: Automata and Logic in Computer Science

• Automata Theory and Formal Language Processing
• Temporal Logic and Verification
• Logic in Program Synthesis and Semantics
• Symbolic Computation
• Model Checking

Chapter 7: Computational Models and Algorithms

• Non-determinism in Computation Models
• Lambda Calculus and Functional Computation
• Petri Nets and State Machines
• Probabilistic Automata and Quantum Automata
• Models of Computation in Biology and Genetics

Chapter 8: Cryptography and Security

• Cryptographic Algorithms and Theoretical Foundations
• Zero-Knowledge Proofs
• Public-Key Cryptography
• Security Protocols and Complexity
• Applications of Computational Theory in Cryptography

Appendices

• A: Glossary of Terms
• B: Further Reading and Resources
• C: Algorithm Complexity Tables
• D: Recommended Software and Tools for Algorithms

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