Data Structures : Time Complexity
Time Complexity Time complexity is a way to describe how the execution time of an algorithm increases as the size of the input grows. It is a measure of algorithm efficiency. Time complexity is usually expressed using Big O notation. ✅ Key Concepts ----------------------- Input Size (n): Represents the amount of data the algorithm is processing. Number of Operations: Refers to the basic steps the algorithm takes (like comparisons, assignments, arithmetic operations, etc). Big O Notation: A mathematical notation used to classify algorithms based on their time complexity. ✅ Common Time Complexities ---------- O(1): Constant Time: The algorithm takes the same amount of time regardless of the input size. Example: Accessing an element in an array by its index. O(log n): Logarithmic Time: The runtime increases logarithmically with the input size. Example: Binary search...