Importance and Applications of Data Structures
Understanding Complexity
Efficiency is measured in two dimensions: time complexity and space complexity. These define how an algorithm scales with input size.
Big O Notation
Big O notation is a mathematical concept used to describe an algorithm's efficiency. It provides a high-level understanding of how an algorithm behaves as the input size grows.
Big O helps us compare algorithms and choose the most appropriate problem. It’s a lens for evaluating the correctness and scalability of our solutions.
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Understanding Complexity
Efficiency is measured in two dimensions: time complexity and space complexity. These define how an algorithm scales with input size.
Big O Notation
Big O notation is a mathematical concept used to describe an algorithm's efficiency. It provides a high-level understanding of how an algorithm behaves as the input size grows.
Big O helps us compare algorithms and choose the most appropriate problem. It’s a lens for evaluating the correctness and scalability of our solutions.
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