COMPUTER SCIENCE AND ENGINEERING
ALGORITHMS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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The amount of time required to solve a particular problem
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How difficult a problem is to solve
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How many lines of code are required to solve a problem
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How quickly a solution can be developed
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Detailed explanation-1: -Time complexity is defined as 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. It is not going to examine the total execution time of an algorithm.
Detailed explanation-2: -So, the time complexity is the number of operations an algorithm performs to complete its task (considering that each operation takes the same amount of time). The algorithm that performs the task in the smallest number of operations is considered the most efficient one in terms of the time complexity.
Detailed explanation-3: -Omega Notation It defines the best case of an algorithm’s time complexity, the Omega notation defines whether the set of functions will grow faster or at the same rate as the expression. Furthermore, it explains the minimum amount of time an algorithm requires to consider all input values.
Detailed explanation-4: -Time Complexity: The time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the length of the input. Note that the time to run is a function of the length of the input and not the actual execution time of the machine on which the algorithm is running on.
Detailed explanation-5: -Time complexity is a function that describes how long an algorithm takes in terms of the quantity of input it receives. Space complexity is a function that describes how much memory (space) an algorithm requires to the quantity of input to the method.