How to calculate the time complexity

The so-called time complexity , It's such a thing ：
Suppose you have a piece of code , The unit of time required to run once is 1, Or writing O（1）, The concrete is 1 individual CPU Execution cycle , still 1 minute , Is not important .
When your input value increases N After times , How much more time ？
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So for a heavy for In a circle , It grows linearly , The number of cycles increases n times , Time also increases n times , So time complexity is O(N)
If it's double for loop , So that is O(N^2), Square relationship .
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Specific to your problem ,
a） A typical heavy for loop
Ask you to write a time complexity is O(N) Code for , Write anything you like , Even if you don't write anything , It is O(N)
b）1) requirement for The time complexity in the loop is O(1), That is, time is not related to N relevant , That directly break Come out .
2） Ask to be j The time complexity increases linearly with exponential growth , The easiest way , Take the ride 2 Except back , again ++
c) Same as B1

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The algorithm basically needs a loop , Recursion, etc ,
Time complexity means that a loop is entering n( May be n Data , It can also be a single value n) The average number of cycles or recursions required for , That is, the number of times the main code is executed