Time Complexity Notations explained:
Omega Notation (Ω-notation)
Omega notation represents the lower bound of the running time of an algorithm. Thus, it provides the best case complexity of an algorithm.
Theta Notation (Θ-notation)
Theta notation encloses the function from above and below. Since it represents the upper and the lower bound of the running time of an algorithm, it is used for analyzing the average-case complexity of an algorithm.
Big-O Notation (O-notation)
Big-O notation represents the upper bound of the running time of an algorithm. Thus, it gives the worst-case complexity of an algorithm.
Time complexity is the amount of time taken by an algorithm to run, as a function of the length of the input. It measures the time taken to execute each statement of code in an algorithm. 🧠 @full_stack_developerz
Omega Notation (Ω-notation)
Omega notation represents the lower bound of the running time of an algorithm. Thus, it provides the best case complexity of an algorithm.
Theta Notation (Θ-notation)
Theta notation encloses the function from above and below. Since it represents the upper and the lower bound of the running time of an algorithm, it is used for analyzing the average-case complexity of an algorithm.
Big-O Notation (O-notation)
Big-O notation represents the upper bound of the running time of an algorithm. Thus, it gives the worst-case complexity of an algorithm.
Time complexity is the amount of time taken by an algorithm to run, as a function of the length of the input. It measures the time taken to execute each statement of code in an algorithm. 🧠 @full_stack_developerz
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