What is algorithm analysis and why is it important?
Algorithm analysis is the study of the efficiency and performance of algorithms. It's important because it helps us understand how algorithms scale with input size and how they compare to one another in terms of time and space complexity.
Can you explain time complexity and space complexity?
Time complexity measures the amount of time an algorithm takes to complete as a function of the input size, 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, O(n log n) for linearithmic 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 that in Big O notation.
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