What is algorithm complexity and why is it important?

What is algorithm complexity and why is it important?

Algorithm complexity refers to the amount of resources required by an algorithm to solve a problem, typically measured in time and space.

Can you explain the difference between time complexity and space complexity?

Time complexity measures how the runtime of an algorithm increases with the size of the input, while space complexity measures the amount of memory an algorithm uses.

What are some common time complexity classes?

Common time complexity classes include O(1) for constant time, O(log n) for logarithmic time, O(n) for linear time, and O(n^2) for quadratic time.

How do I analyze the complexity of an algorithm?

To analyze an algorithm's complexity, you can count the number of basic operations it performs as a function of the input size and express it using Big O notation.