WGU C949 OBJECTIVE ASSESSMENT EXAM 2
TEST PAPER SOLVED QUESTIONS
◉ O(N log N). Answer: Heap Sort Time Complexity
◉ Radix Sort. Answer: A sort type that sorts by hashing values to
buckets based on individual digits such as the 1's place, then
combines into array, then hashes again using the 10's, 100's, etc.
◉ O(nk) where K = number of digits in largest number.. Answer:
Radix Sort Time Complexity
◉ Shell Sort. Answer: Generalization of insertion sort but also uses a
gap value. Sorts elements farther apart and reduces the gap.
◉ O(N^2). Answer: Time Complexity of Shell Sort
◉ Bubble, Selection, Insertion. Answer: Sort types good for small
datasets.
◉ Merge, Quicksort, Heap. Answer: Sort types better for larger
datasets
, ◉ Big O Notation. Answer: Allows for comparing the efficiency of
algorithms.
◉ O(1). Answer: The algorithm takes the same amount of time to
execute regardless of the size of the input. - Constant
◉ O(Log N). Answer: The runtime increases logarithmically as the
input size increases. Typically occurs in algorithms that halve the
problem size at each step, like binary search.
◉ O(N log N). Answer: The runtime increases more than linearly but
less than quadratically. Common in efficient sorting algorithms like
merge sort and quicksort. Efficient for large datasets
◉ O(N^2). Answer: The runtime increases quadratically with the
size of the input. If you double the input size, the runtime
quadruples.
◉ O(2^N). Answer: The runtime doubles with each additional
element in the input. Common in algorithms that solve problems by
brute force or explore all possible solutions. - Exponential
◉ O(2n) simplifies to O(n). Answer: What does O(2n) simplify to?
TEST PAPER SOLVED QUESTIONS
◉ O(N log N). Answer: Heap Sort Time Complexity
◉ Radix Sort. Answer: A sort type that sorts by hashing values to
buckets based on individual digits such as the 1's place, then
combines into array, then hashes again using the 10's, 100's, etc.
◉ O(nk) where K = number of digits in largest number.. Answer:
Radix Sort Time Complexity
◉ Shell Sort. Answer: Generalization of insertion sort but also uses a
gap value. Sorts elements farther apart and reduces the gap.
◉ O(N^2). Answer: Time Complexity of Shell Sort
◉ Bubble, Selection, Insertion. Answer: Sort types good for small
datasets.
◉ Merge, Quicksort, Heap. Answer: Sort types better for larger
datasets
, ◉ Big O Notation. Answer: Allows for comparing the efficiency of
algorithms.
◉ O(1). Answer: The algorithm takes the same amount of time to
execute regardless of the size of the input. - Constant
◉ O(Log N). Answer: The runtime increases logarithmically as the
input size increases. Typically occurs in algorithms that halve the
problem size at each step, like binary search.
◉ O(N log N). Answer: The runtime increases more than linearly but
less than quadratically. Common in efficient sorting algorithms like
merge sort and quicksort. Efficient for large datasets
◉ O(N^2). Answer: The runtime increases quadratically with the
size of the input. If you double the input size, the runtime
quadruples.
◉ O(2^N). Answer: The runtime doubles with each additional
element in the input. Common in algorithms that solve problems by
brute force or explore all possible solutions. - Exponential
◉ O(2n) simplifies to O(n). Answer: What does O(2n) simplify to?
