designed an iterative algorithm for separating n VLSI chips into those that are good and those that are bad by testing two chips at a time and learning either that they are the same or that they are different. To help, at least half of the chips are promised to be good. Now design (much easier) a randomized algorithm for this problem. Here are some hints.
Randomly select one of the chips. What is the probability that the chip is good?
How can you learn whether or not the selected chip is good?
If it is good, how can you easily partition the chips into good and bad chips?
If the chip is not good, what should your algorithm do?
When should the algorithm stop?
What is the expected running time of this algorithm?

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Time Complexity

In computer science, the computational complexity that is measured in terms of time is referred to as time complexity that defines how long it takes a computer to execute an algorithm. An algorithm's time complexity is measured by the the amount of time required to execute each statement of code in the algorithm. If a statement is set to execute repetitively, the number of times it will be N multiplied by the time it takes to run that function each time is equal .