WGU C949 Data Structures and Algorithms
Practice Study Guide Questions with
Distinction level Marking scheme version
2024/2025
An algorithm's best case - correct answer is the scenario
where the algorithm does the minimum possible number of
operations.
An algorithm's worst case - correct answer is the scenario
where the algorithm does the maximum possible number of
operations.
The variable value N - correct answer cannot be replaced
with a constant of 0 to describe a best case scenario. A best case
scenario must describe the contents of the data being processed.
Lower bound: - correct answer A function f(N) that is ≤ the
best case T(N), for all values of N ≥ 1.
Upper bound - correct answer A function f(N) that is ≥ the
worst case T(N), for all values of N ≥ 1
Upper Bound for algorithms - correct answer An algorithm's
worst case runtime complexity is always an upper bound for the
algorithm.
,Lower Bound for an algorithm - correct answer An
algorithm's best case runtime complexity is always a lower
bound for the algorithm.
Asymptotic notation - correct answer Is the classification of
runtime complexity that uses functions that indicate only the
growth rate of a bounding function.
Asymptotic notation: O notation - correct answer provides a
growth rate for an algorithm's upper bound.
Asymptotic notation: Ω notation - correct answer provides a
growth rate for an algorithm's lower bound.
Asymptotic notation: Θ notation - correct answer provides a
growth rate that is both an upper and lower bound.
Linear search - correct answer may require searching all list
elements, which can lead to long runtimes.
Binary Search - correct answer is a faster algorithm for
searching a list if the list's elements are sorted and directly
accessible (such as an array). Binary search first checks the
middle element of the list. If the search key is found, the
algorithm returns the matching location. If the search key is not
found, the algorithm repeats the search on the remaining left
sublist (if the search key was less than the middle element) or
the remaining right sublist (if the search key was greater than
the middle element).
,Binary search equation - correct answer log2(Size of
elements) + 1
Selection sort - correct answer is a sorting algorithm that
treats the input as two parts, a sorted part and an unsorted part,
and repeatedly selects the proper next value to move from the
unsorted part to the end of the sorted part.
Selection sort, comparing sort times - correct answer A list
with twice as many elements requires 4 times as many
comparisons.
Insertion sort - correct answer is a sorting algorithm that
treats the input as two parts, a sorted part and an unsorted part,
and repeatedly inserts the next value from the unsorted part into
the correct location in the sorted part.
Insertion sort's typical runtime is - correct answer O(N^2)
A nearly sorted list - correct answer only contains a few
elements not in sorted order. Ex: (4, 5, 17, 25, 89, 14) is nearly
sorted having only one element not in sorted position.
Shell sort - correct answer is a sorting algorithm that treats
the input as a collection of interleaved lists, and sorts each list
individually with a variant of the insertion sort algorithm.
, Shell sort: Gap Value - correct answer The gap value equals
the number of interleaved lists.
ShellSort will properly sort an array using any collection of gap
values, provided the collection contains - correct answer True
Quicksort - correct answer is a sorting algorithm that
repeatedly partitions the input into low and high parts (each part
unsorted), and then recursively sorts each of those parts.
Quicksort: midpoint - correct answer lowIndex + (highIndex -
lowIndex) / 2
The quicksort algorithm's runtime - correct answer is
typically O(N log N)
Quicksort: Sorted partitions - correct answer The elements
within each part can be in any order once the algorithm
completes. The only requirement is that all elements in the left
partition are less than or equal to all elements in the right
partition.
Merge sort - correct answer is a sorting algorithm that
divides a list into two halves, recursively sorts each half, and
then merges the sorted halves to produce a sorted list. The
recursive partitioning continues until a list of 1 element is
reached, as list of 1 element is already sorted.
Practice Study Guide Questions with
Distinction level Marking scheme version
2024/2025
An algorithm's best case - correct answer is the scenario
where the algorithm does the minimum possible number of
operations.
An algorithm's worst case - correct answer is the scenario
where the algorithm does the maximum possible number of
operations.
The variable value N - correct answer cannot be replaced
with a constant of 0 to describe a best case scenario. A best case
scenario must describe the contents of the data being processed.
Lower bound: - correct answer A function f(N) that is ≤ the
best case T(N), for all values of N ≥ 1.
Upper bound - correct answer A function f(N) that is ≥ the
worst case T(N), for all values of N ≥ 1
Upper Bound for algorithms - correct answer An algorithm's
worst case runtime complexity is always an upper bound for the
algorithm.
,Lower Bound for an algorithm - correct answer An
algorithm's best case runtime complexity is always a lower
bound for the algorithm.
Asymptotic notation - correct answer Is the classification of
runtime complexity that uses functions that indicate only the
growth rate of a bounding function.
Asymptotic notation: O notation - correct answer provides a
growth rate for an algorithm's upper bound.
Asymptotic notation: Ω notation - correct answer provides a
growth rate for an algorithm's lower bound.
Asymptotic notation: Θ notation - correct answer provides a
growth rate that is both an upper and lower bound.
Linear search - correct answer may require searching all list
elements, which can lead to long runtimes.
Binary Search - correct answer is a faster algorithm for
searching a list if the list's elements are sorted and directly
accessible (such as an array). Binary search first checks the
middle element of the list. If the search key is found, the
algorithm returns the matching location. If the search key is not
found, the algorithm repeats the search on the remaining left
sublist (if the search key was less than the middle element) or
the remaining right sublist (if the search key was greater than
the middle element).
,Binary search equation - correct answer log2(Size of
elements) + 1
Selection sort - correct answer is a sorting algorithm that
treats the input as two parts, a sorted part and an unsorted part,
and repeatedly selects the proper next value to move from the
unsorted part to the end of the sorted part.
Selection sort, comparing sort times - correct answer A list
with twice as many elements requires 4 times as many
comparisons.
Insertion sort - correct answer is a sorting algorithm that
treats the input as two parts, a sorted part and an unsorted part,
and repeatedly inserts the next value from the unsorted part into
the correct location in the sorted part.
Insertion sort's typical runtime is - correct answer O(N^2)
A nearly sorted list - correct answer only contains a few
elements not in sorted order. Ex: (4, 5, 17, 25, 89, 14) is nearly
sorted having only one element not in sorted position.
Shell sort - correct answer is a sorting algorithm that treats
the input as a collection of interleaved lists, and sorts each list
individually with a variant of the insertion sort algorithm.
, Shell sort: Gap Value - correct answer The gap value equals
the number of interleaved lists.
ShellSort will properly sort an array using any collection of gap
values, provided the collection contains - correct answer True
Quicksort - correct answer is a sorting algorithm that
repeatedly partitions the input into low and high parts (each part
unsorted), and then recursively sorts each of those parts.
Quicksort: midpoint - correct answer lowIndex + (highIndex -
lowIndex) / 2
The quicksort algorithm's runtime - correct answer is
typically O(N log N)
Quicksort: Sorted partitions - correct answer The elements
within each part can be in any order once the algorithm
completes. The only requirement is that all elements in the left
partition are less than or equal to all elements in the right
partition.
Merge sort - correct answer is a sorting algorithm that
divides a list into two halves, recursively sorts each half, and
then merges the sorted halves to produce a sorted list. The
recursive partitioning continues until a list of 1 element is
reached, as list of 1 element is already sorted.
