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Data Structures and Algorithms ​

Data structures and algorithms are the heart of computer science. Data structures define how data is organized and stored, while algorithms are the procedures and instructions used to solve specific problems.

Core Concepts ​

1. Basic Data Structures ​

  • Array: Continuous memory space, fast random access.
  • LinkedList: Non-continuous space, efficient insertion and deletion.
  • Stack: Last-In-First-Out (LIFO).
  • Queue: First-In-First-Out (FIFO).

2. Advanced Data Structures ​

  • Tree: Including Binary Trees, AVL Trees, Red-Black Trees, and B-Trees.
  • Graph: Studying relationships between nodes and edges, featuring BFS and DFS.
  • Hash Table: Achieves O(1) average lookup time via hash functions.

3. Key Algorithms ​

  • Sorting: Bubble, Selection, Insertion, Quick Sort, Merge Sort, Heap Sort.
  • Searching: Binary Search, Binary Search Tree lookup.
  • Dynamic Programming (DP): Solving overlapping subproblems and optimal substructure.
  • Greedy Algorithms: Taking the local optimum at each step.
  • Divide and Conquer: Breaking large problems into independent smaller ones.

Mastering data structures and algorithms is essential for every developer.