Is this a Proper “Rule” for Identifying the “Big O” Notation of an Algorithm?
I’ve been learning more about Big O Notation and how to calculate it based on how an algorithm is written. I came across an interesting set of “rules” for calculating an algorithms Big O notation and I wanted to see if I’m on the right track or way off.
Notation for the average time complexity of an algorithm
What notation do you use for the average time complexity of an algorithm? It occurs to me that the proper way would be to use big-theta to refer to a set of results (even when a specific try may differ). For example, average array search would be Θ(n+1)/2.
Change of the complexity class through compiler optimization?
I am looking for an example where an algorithm is apparently changing its complexity class due to compiler and/or processor optimization strategies.
Change of the complexity class through compiler optimization?
I am looking for an example where an algorithm is apparently changing its complexity class due to compiler and/or processor optimization strategies.
Change of the complexity class through compiler optimization?
I am looking for an example where an algorithm is apparently changing its complexity class due to compiler and/or processor optimization strategies.
Change of the complexity class through compiler optimization?
I am looking for an example where an algorithm is apparently changing its complexity class due to compiler and/or processor optimization strategies.
Change of the complexity class through compiler optimization?
I am looking for an example where an algorithm is apparently changing its complexity class due to compiler and/or processor optimization strategies.
What is the big-O cpu time of Euclid’s Algorithm of “Greatest common divisor of two numbers”
Looking at Euclid’s algorithm for the “Greatest common divisor of two numbers”, I’m trying to divine the big-O cpu time for numbers K, and N. Can anybody help?
What is the big-O cpu time of Euclid’s Algorithm of “Greatest common divisor of two numbers”
Looking at Euclid’s algorithm for the “Greatest common divisor of two numbers”, I’m trying to divine the big-O cpu time for numbers K, and N. Can anybody help?
Time-complexity of nested for loop
I have loops like this: