WGU C949 DATA STRUCTURES
AND ALGORITHMS I OA 2026 | 150
PRACTICE QUESTIONS WITH
PRENIUM EXAM
110 Questions with Answers and Detailed Rationales
100 PERCENT GUARANTEED PASS
INSTANT DOWNLOAD ANSWERS INCLUDED
IMPORTANCE OF THIS DOCUMENT
This comprehensive examination preparation guide has been meticulously developed to help you succeed in the
WGU C949 DATA STRUCTURES AND ALGORITHMS I OA 2026 | 150 PRACTICE QUESTIONS WITH
ANSWERS & RATIONALES + 2 MOCK EXAMS | COMPLETE STUDY GUIDE.. It contains 110 carefully selected
questions that reflect the most current exam content and testing strategies. Each question is accompanied by a
correct answer and a detailed rationale that explains the underlying pathophysiology, pharmacology, or clinical
reasoning.
Self-Assessment – Test your knowledge and Exam Preparation – Familiarize yourself with the
identify areas requiring further question format and content
study areas
Concept Reinforcement – Deepen your Confidence Building – Develop test-taking
understanding through strategies and reduce
evidence-based exam anxiety
rationales
Time Management – Practice answering
questions under simulated
exam conditions
Review Summary 110 Questions
Foundations - Application - WGU C949 DATA Structures AND Algorithms I OA 2026 150 WITH &
Rationales 2 Exams Complete Study Guide DATA Structures AND Algorithms Undergraduate YEAR 3 /
Graduate
All answers with rationales
,Table of Contents
Content Area Questions Key Topics
Algorithm Analysis AND 1-19 TIME Complexity, Algorithm, Graph, Minimum, Worst-case TIME
Big-o Notation
DATA Structures Arrays 20-38 Graph, Worst-case TIME, Search, Traversal, TIME Complexity
Linked Lists Stacks AND
Queues
Trees AND TREE Traversals 39-57 Graph, Array, B-tree, Order, Directed
HASH Tables AND Hashing 58-76 Search, Array, Algorithm, Primary, HASH Table
Techniques
Sorting Algorithms 77-95 Array, Algorithm, Function, Search, Binary
Searching Algorithms 96-110 Dynamic, Traversal, Programming, Number, Nodes
TOTAL 110 All questions include answers and detailed rationales
,Section A - Algorithm Analysis AND Big-o Notation
Q1.
In a max-heap of size n, which operation has the best asymptotic worst-case time
complexity?
A. Increase-key B. Delete-max
C. Find-max D. Build-heap
Correct: C - Find-max
Rationale:Find-max is O(1) because the maximum is always at the root. Increase-key and
delete-max are O(log n), and build-heap is O(n). Thus, find-max is asymptotically the fastest.
Q2.
Which tree traversal of a binary search tree produces the keys in sorted order?
A. Preorder B. Inorder
C. Postorder D. Level-order
Correct: B - Inorder
Rationale:Inorder traversal visits the left subtree, then the node, then the right subtree, which
yields keys in ascending order for a BST. Preorder, postorder, and level-order do not produce
sorted order.
Q3.
Which sorting algorithm has the best average-case time complexity?
A. Bubble sort B. Insertion sort
C. Merge sort D. Selection sort
Correct: C - Merge sort
Rationale:Merge sort has O(n log n) average-case time, while bubble, insertion, and
selection sorts all have O(n^2) average-case time. Thus, merge sort is asymptotically faster.
Q4.
In a hash table with open addressing, what is the primary cause of clustering?
A. Poor hash function B. Too many collisions
C. Resizing the table D. Using separate chaining
Page 3
, Section A - Algorithm Analysis AND Big-o Notation
Correct: B - Too many collisions
Rationale:Clustering occurs when many keys hash to the same or nearby slots, leading to
long probe sequences. A poor hash function can cause clustering, but the primary cause is
the accumulation of collisions. Resizing and separate chaining are not direct causes.
Q5.
Which graph algorithm can be used to detect a cycle in a directed graph?
A. Breadth-first search (BFS) B. Depth-first search (DFS)
C. Dijkstra's algorithm D. Kruskal's algorithm
Correct: B - Depth-first search (DFS)
Rationale:DFS can detect cycles in directed graphs by identifying back edges during
traversal. BFS can detect cycles in undirected graphs but not reliably in directed ones.
Dijkstra's finds shortest paths, and Kruskal's finds minimum spanning trees.
Q6.
What is the worst-case time complexity of quicksort?
A. O(n log n) B. O(n)
C. O(n^2) D. O(log n)
Correct: C - O(n^2)
Rationale:Quicksort degrades to O(n^2) when partitions are highly unbalanced, such as
when the pivot is always the smallest or largest element. Randomized or median-of-three
pivoting avoids this in practice.
Q7.
Which data structure is most efficient for implementing a priority queue?
A. Array B. Linked list
C. Binary heap D. Binary search tree
Correct: C - Binary heap
Rationale:Binary heaps provide O(log n) insert and delete-max/min, which is optimal for
priority queues. Arrays and linked lists have O(n) for at least one operation, and BSTs can
degrade to O(n) if unbalanced.
Page 4
AND ALGORITHMS I OA 2026 | 150
PRACTICE QUESTIONS WITH
PRENIUM EXAM
110 Questions with Answers and Detailed Rationales
100 PERCENT GUARANTEED PASS
INSTANT DOWNLOAD ANSWERS INCLUDED
IMPORTANCE OF THIS DOCUMENT
This comprehensive examination preparation guide has been meticulously developed to help you succeed in the
WGU C949 DATA STRUCTURES AND ALGORITHMS I OA 2026 | 150 PRACTICE QUESTIONS WITH
ANSWERS & RATIONALES + 2 MOCK EXAMS | COMPLETE STUDY GUIDE.. It contains 110 carefully selected
questions that reflect the most current exam content and testing strategies. Each question is accompanied by a
correct answer and a detailed rationale that explains the underlying pathophysiology, pharmacology, or clinical
reasoning.
Self-Assessment – Test your knowledge and Exam Preparation – Familiarize yourself with the
identify areas requiring further question format and content
study areas
Concept Reinforcement – Deepen your Confidence Building – Develop test-taking
understanding through strategies and reduce
evidence-based exam anxiety
rationales
Time Management – Practice answering
questions under simulated
exam conditions
Review Summary 110 Questions
Foundations - Application - WGU C949 DATA Structures AND Algorithms I OA 2026 150 WITH &
Rationales 2 Exams Complete Study Guide DATA Structures AND Algorithms Undergraduate YEAR 3 /
Graduate
All answers with rationales
,Table of Contents
Content Area Questions Key Topics
Algorithm Analysis AND 1-19 TIME Complexity, Algorithm, Graph, Minimum, Worst-case TIME
Big-o Notation
DATA Structures Arrays 20-38 Graph, Worst-case TIME, Search, Traversal, TIME Complexity
Linked Lists Stacks AND
Queues
Trees AND TREE Traversals 39-57 Graph, Array, B-tree, Order, Directed
HASH Tables AND Hashing 58-76 Search, Array, Algorithm, Primary, HASH Table
Techniques
Sorting Algorithms 77-95 Array, Algorithm, Function, Search, Binary
Searching Algorithms 96-110 Dynamic, Traversal, Programming, Number, Nodes
TOTAL 110 All questions include answers and detailed rationales
,Section A - Algorithm Analysis AND Big-o Notation
Q1.
In a max-heap of size n, which operation has the best asymptotic worst-case time
complexity?
A. Increase-key B. Delete-max
C. Find-max D. Build-heap
Correct: C - Find-max
Rationale:Find-max is O(1) because the maximum is always at the root. Increase-key and
delete-max are O(log n), and build-heap is O(n). Thus, find-max is asymptotically the fastest.
Q2.
Which tree traversal of a binary search tree produces the keys in sorted order?
A. Preorder B. Inorder
C. Postorder D. Level-order
Correct: B - Inorder
Rationale:Inorder traversal visits the left subtree, then the node, then the right subtree, which
yields keys in ascending order for a BST. Preorder, postorder, and level-order do not produce
sorted order.
Q3.
Which sorting algorithm has the best average-case time complexity?
A. Bubble sort B. Insertion sort
C. Merge sort D. Selection sort
Correct: C - Merge sort
Rationale:Merge sort has O(n log n) average-case time, while bubble, insertion, and
selection sorts all have O(n^2) average-case time. Thus, merge sort is asymptotically faster.
Q4.
In a hash table with open addressing, what is the primary cause of clustering?
A. Poor hash function B. Too many collisions
C. Resizing the table D. Using separate chaining
Page 3
, Section A - Algorithm Analysis AND Big-o Notation
Correct: B - Too many collisions
Rationale:Clustering occurs when many keys hash to the same or nearby slots, leading to
long probe sequences. A poor hash function can cause clustering, but the primary cause is
the accumulation of collisions. Resizing and separate chaining are not direct causes.
Q5.
Which graph algorithm can be used to detect a cycle in a directed graph?
A. Breadth-first search (BFS) B. Depth-first search (DFS)
C. Dijkstra's algorithm D. Kruskal's algorithm
Correct: B - Depth-first search (DFS)
Rationale:DFS can detect cycles in directed graphs by identifying back edges during
traversal. BFS can detect cycles in undirected graphs but not reliably in directed ones.
Dijkstra's finds shortest paths, and Kruskal's finds minimum spanning trees.
Q6.
What is the worst-case time complexity of quicksort?
A. O(n log n) B. O(n)
C. O(n^2) D. O(log n)
Correct: C - O(n^2)
Rationale:Quicksort degrades to O(n^2) when partitions are highly unbalanced, such as
when the pivot is always the smallest or largest element. Randomized or median-of-three
pivoting avoids this in practice.
Q7.
Which data structure is most efficient for implementing a priority queue?
A. Array B. Linked list
C. Binary heap D. Binary search tree
Correct: C - Binary heap
Rationale:Binary heaps provide O(log n) insert and delete-max/min, which is optimal for
priority queues. Arrays and linked lists have O(n) for at least one operation, and BSTs can
degrade to O(n) if unbalanced.
Page 4
