COMP 272
Data Structures and Algorithms Mastery Quiz
Test your knowledge of essential data structures and algorithms with our comprehensive quiz! This quiz covers a range of topics including heaps, sorting algorithms, graph theory, and hash maps.
- 26 carefully crafted questions
- Multiple choice format
- Ideal for students and professionals alike
The expected time complexity for a HashMap/Table is...
O (n log n)
O(n)
O(1)
O(log n)
The worst time complexity to search/insert/remove a HashMap/Table is...
O (n log n)
O(n)
O(1)
O(log n)
In practice, hashing is very fast provided the load factor is not close to 100%
True
False
The time complexity to insert/remove for Heaps are...
O (n log n)
O(n)
O(1)
O(log n)
The last node of a heap is the rightmost node of maximum depth
True
False
A heap storing n keys has a height of....
O (n log n)
O(n)
O(1)
O(log n)
The time complexity to look at the smallest value (Peak) for Heaps are...
O (n log n)
O(n)
O(1)
O(log n)
Since a heap has height O(log n), upheap runs in O(log n) time
True
False
Since a heap has height O(log n), downheap runs in O(log n) time
True
False
Using a heap-based priority queue, the time complexity for a sort sequence (heap-sort) of n elements is...
O (n log n)
O(n)
O(1)
O(log n)
The time complexity for a Heap Sort is...
O (n log n)
O(n)
O(1)
O(log n)
Merge Sort and QuickSort are two of the most efficient sorting algorithm in practice
True
False
The time complexity for a Merge Sort is...
O (n log n)
O(n)
O(1)
O(log n)
Merge and quick sort complexity stays the same.
True
False
Merging two sorted sequences, each with n/2 elements and implemented by means of a doubly linked list, takes ....
O (n log n)
O(n)
O(1)
O(log n)
The worst-case running time of quick sort is....
O (n^2)
O(n)
O(1)
O(log n)
The expected running time for selection-sort & insertion-sort is...
O (n^2)
O(n)
O(1)
O(log n)
The expected running time of the quick-sort is...
O (n log n)
O(n)
O(1)
O(log n)
The expected running time of the sorting the lower bound is...
O (n log n)
O(n)
O(1)
O(log n)
The expected running time of Depth-First Search on a graph with N vertices and M edges is...
O(n)
O (m)
O(n+m)
O(1)
Setting/getting a vertex/edge label for DFS takes...
O(n)
O (m)
O(n+m)
O(1)
The expected running time of Breadth-First Search on a graph with N vertices and M edges is...
O(n)
O (m)
O(n+m)
O(1)
Setting/getting a vertex/edge label for BFS takes...
O(n)
O (m)
O(n+m)
O(1)
For Graph performance, which is the best run time
Edge List
Adjacency List
Adjacency Matrix
Dijkstra’s algorithm takes....
O(n)
O (m)
O((n+m) log n)
O(1)
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