Importance of Algorithms
- Fact: Algorithms are step-by-step procedures or formulas for solving problems. They form the heart of any computational solution.
- Example:
- Binary Search Algorithm: An efficient search algorithm that divides the search interval in half, significantly reducing the search space.
Python3
# Example: Binary Search Algorithm def binary_search(arr, target): low, high = 0 , len (arr) - 1 while low < = high: mid = (low + high) / / 2 if arr[mid] = = target: return mid elif arr[mid] < target: low = mid + 1 else : high = mid - 1 return - 1 |
Output
25 Interesting DSA Terms/Concepts Every Programmer Should Know
Data Structures and Algorithms (DSA) form the backbone of computer science, playing a pivotal role in efficient problem-solving and software development. Here are 25 interesting Data Structures and Algorithms (DSA) terms/concepts that every programmer should know. Understanding these concepts is crucial for developing efficient algorithms and solving a variety of programming challenges.
Table of Content
- Definition of Data Structure
- Types of Data Structures
- Importance of Algorithms
- Dynamic Arrays
- Linked Lists
- Time Complexity
- Space Complexity
- Tree Structures
- Hash Tables
- Graphs
- Searching Algorithms
- Sorting Algorithms
- Dynamic Programming
- Divide and Conquer
- NP-Completeness
- Heaps
- Trie Data Structure
- B-Trees
- AVL Trees
- In-Place Algorithms
- Bellman-Ford Algorithm
- Floyd-Warshall Algorithm
- Dijkstra’s Algorithm
- Big-O Notation
- NP-Hard Problems
Let’s delve into 25 intriguing concepts of DSA, each accompanied by detailed examples for a comprehensive understanding.
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