What is time complexity and space complexity
Time complexity is defined as the amount of time it takes a program to run. Space complexity is the space used by a program. (wikipedia).
The time complexity of a program is defined as the number of operations that have to be performed per input. Space complexity is the amount of space required by a given program or algorithm.
Typically, we want programs with low space and time requirements. These are also known as optimal algorithms or efficient algorithms. Such an algorithm might take 2n operations to complete with n as its input size.
Space complexity of an algorithm is typically expressed in terms of the number of memory cells it uses, the number of registers it uses or the number of pages it occupies in virtual memory.
How do you measure time complexity and space complexity
To measure time complexity you must write a program and use a stop watch to time the run. This measures the amount of seconds it takes to complete. To measure space complexity you would do the same thing but use a calculator, this measures how much memory the program uses. The more memory the program uses, the less time it will take to complete. To measure space complexity you must use a calculator because if you did the same thing with a stop watch, it would measure the amount of time it takes to complete.
Another way to measure time complexity is by using a calculator for measuring space complexity and a stop watch for measuring time complexity. I feel that this is not effective because the two numbers may be different and the number could be inaccurate. There are many factors that can effect how much time or how much memory your program uses such a bad coding, or an out of date computer.
What are some examples of time complexity and space complexity
x = 1e-5 x = 1e-6 x = 1e-7 x = 1e-8 x = 1e-9 x = 10000000000000 x = 1000000000000 x = 10000000000 x = 100000000 x = 10000 x = 1000 x = 100 x = 10 x = 1
time complexity vs space complexity:
This can be difficult to understand, but one thing you will know for certain is that there are many different types of complexities in computer software. Time and space complexities can be helpful if you’re trying to determine whether an algorithm or problem might be a good fit for your project. These two factors, combined with other considerations such as computing resources, are often seen as the triad of trade-offs engineers must make when they decide on developing their next big hit.