Data Structures and Algorithms in C 1st edition by Adam Drozdek ASIN B002WLXMBY

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ASIN:       B002WLXMBY
Author:         Adam Drozdek

 Data Structures & Algorithms in C++ 1st Table of contents:

1. Arrays and Strings

   • Introduction to Arrays
   • Operations on Arrays (Insertion, Deletion, Searching)
   • Multi-dimensional Arrays
   • Strings and String Manipulation in C++

2. Linked Lists

   • Singly Linked Lists
   • Doubly Linked Lists
   • Circular Linked Lists
   • Operations on Linked Lists (Insertion, Deletion, Traversal)

3. Stacks and Queues

   • Introduction to Stacks
   • Stack Operations and Applications
   • Introduction to Queues
   • Queue Operations and Applications (Circular Queues, Priority Queues)

4. Trees

   • Introduction to Trees and Terminology
   • Binary Trees
   • Binary Search Trees (BST)
   • AVL Trees and Rotations
   • Tree Traversals (Pre-order, In-order, Post-order)

5. Heaps

   • Introduction to Heaps
   • Binary Heaps (Min-Heap, Max-Heap)
   • Heap Operations (Insertion, Deletion)
   • Applications of Heaps (Priority Queue)

6. Hashing

   • Hash Tables and Hash Functions
   • Collision Resolution Techniques (Chaining, Open Addressing)
   • Applications of Hashing

7. Graphs

   • Introduction to Graphs and Terminology
   • Representation of Graphs (Adjacency Matrix, Adjacency List)
   • Graph Traversal Algorithms (BFS, DFS)
   • Shortest Path Algorithms (Dijkstra’s, Bellman-Ford)
   • Minimum Spanning Tree Algorithms (Prim’s, Kruskal’s)

8. Searching Algorithms

   • Linear Search and Binary Search
   • Time Complexity of Searching Algorithms
   • Advanced Searching Techniques (Interpolation Search)

9. Sorting Algorithms

   • Bubble Sort, Selection Sort, Insertion Sort
   • Merge Sort, Quick Sort, Heap Sort
   • Radix Sort and Bucket Sort
   • Sorting Complexity Analysis

10. Divide and Conquer

    • The Divide and Conquer Paradigm
    • Solving Problems using Divide and Conquer (Merge Sort, Quick Sort)
    • Optimization Techniques in Divide and Conquer

11. Dynamic Programming

    • Introduction to Dynamic Programming
    • Memoization and Tabulation Techniques
    • Solving Classic Problems (Knapsack Problem, Longest Common Subsequence)

12. Greedy Algorithms

    • Introduction to Greedy Algorithms
    • Greedy Techniques for Problem Solving
    • Solving Classic Problems (Fractional Knapsack, Huffman Coding)

13. Backtracking

    • Introduction to Backtracking Algorithms
    • Solving Problems Using Backtracking (N-Queens, Subset Sum)
    • Complexity Analysis of Backtracking Algorithms

14. Graph Algorithms – Advanced Topics

    • Topological Sorting
    • Strongly Connected Components (Kosaraju’s Algorithm)
    • Network Flow Algorithms (Ford-Fulkerson, Edmonds-Karp)

15. Advanced Data Structures

    • Segment Trees and Applications
    • Fenwick Tree (Binary Indexed Tree)
    • Disjoint Set Union (Union-Find)
    • Suffix Arrays and Suffix Trees

16. String Algorithms

    • Pattern Matching Algorithms (Naive, KMP, Rabin-Karp)
    • Trie Data Structure
    • Regular Expressions and Automata

17. Complexity Analysis

    • Time and Space Complexity Analysis
    • Big O Notation, Omega Notation, Theta Notation
    • Analyzing the Efficiency of Algorithms

18. Applications of Data Structures and Algorithms

    • Real-world Applications (Database Indexing, Memory Management)
    • Problem-Solving with Data Structures and Algorithms
    • Case Studies and Problem-Solving Techniques
19.  

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