Western Governors University (WGU) ICSC2100 C949 Data Structures and Algorithms I Practice Exam

The term that refers to an algorithm where the input size directly correlates with the number of operations is linear time. In a linear time algorithm, when you increase the size of the input, the number of operations required also increases proportionally. This can often be seen in simple loops that iterate through the entire input data set, performing a constant time operation for each element.

For example, if you have an array of size \( n \) and your algorithm requires you to look at each element exactly once, the total number of operations will be \( n \). Therefore, the time complexity is expressed as \( O(n) \), indicating that the time taken grows linearly with the input size.

This contrasts with constant time, where the number of operations does not change regardless of input size; logarithmic time, where the number of operations grows logarithmically in relation to input size; and quadratic time, where the number of operations grows with the square of the input size. In these other types, the relationship between input size and operations is not direct and linear.