In DFS, what data structure is typically used to keep track of visited nodes?
- Heap
- Linked List
- Queue
- Stack
In Depth-First Search (DFS), a stack is typically used to keep track of visited nodes. The stack follows the Last In, First Out (LIFO) principle, ensuring that the last node visited is the first one to be explored.
How can memoization be used to optimize the computation of Fibonacci numbers?
- By implementing a randomized algorithm to generate Fibonacci numbers.
- By sorting the Fibonacci sequence in ascending order before computation.
- By storing previously computed Fibonacci numbers in a table and reusing them to avoid redundant calculations.
- By using a divide and conquer approach to split the Fibonacci sequence into smaller subproblems.
Memoization optimizes the computation of Fibonacci numbers by storing previously calculated values in a table (memory). When a Fibonacci number is needed, the algorithm first checks if it's already in the table, and if so, retrieves the precomputed value, avoiding redundant recursive calculations.
An efficient way to handle deletions in a hash table is to use a _______ value to mark deleted entries, allowing for proper rehashing.
- Null
- Sentinel
- Special marker
- Unique key
An efficient way to handle deletions in a hash table is to use a special marker value to mark deleted entries. This allows for proper rehashing and ensures that the deleted entries are correctly accounted for during subsequent operations.
Which of the following best describes the selection sort algorithm?
- Algorithm based on priority queues
- In-place algorithm with no comparisons
- Recursive algorithm using subproblems
- Sorting algorithm that divides the list into two parts: sorted and unsorted
The selection sort algorithm is a simple sorting algorithm that divides the input list into two parts: a sorted and an unsorted portion. It repeatedly selects the smallest (or largest) element from the unsorted part and swaps it with the first element of the unsorted part.
One application of DFS is in _______ _______ problems.
- Dynamic programming
- Pathfinding and graph traversal
- Solving optimization
- Sorting and searching
One application of DFS is in pathfinding and graph traversal problems. It is commonly used to find paths between nodes in a graph or to explore all nodes in a graph.
suitable for sorting data with a fixed _______ because it processes each digit separately.
- Key
- Radix
- Range
- Size
Radix sort is suitable for sorting data with a fixed size because it processes each digit separately, allowing it to handle numbers with varying lengths in a more efficient manner.
In a priority queue, how are elements arranged for retrieval?
- Always in ascending order.
- Based on a specific priority assigned to each element.
- Based on the order of insertion.
- Randomly arranged.
In a priority queue, elements are arranged for retrieval based on a specific priority assigned to each element. The element with the highest priority is retrieved first. This ensures that higher-priority elements take precedence over lower-priority ones.
Bellman-Ford algorithm can handle graphs with _______ edge weights and detect _______ weight cycles.
- Constant, Positive
- Uniform, Positive
- Variable, Negative
- Varying, Negative
Bellman-Ford algorithm can handle graphs with variable edge weights and detect negative weight cycles. It is capable of handling graphs with both positive and negative edge weights, making it suitable for a wider range of scenarios compared to some other algorithms.
What are some optimizations that can be applied to improve the efficiency of the Edit Distance algorithm?
- Ignoring the order of characters in the strings
- Increasing the size of input strings
- Using a brute-force approach for each pair of characters
- Using memoization to store and reuse intermediate results
Memoization is an optimization technique where intermediate results are stored, preventing redundant calculations and significantly improving the efficiency of the Edit Distance algorithm.
search is an informed search algorithm that combines the advantages of _______ and _______ search algorithms.
- Breadth-first, Depth-first
- Breadth-first, Dijkstra's
- Greedy, Depth-first
- Greedy, Dijkstra's
A* search combines the advantages of the Greedy algorithm, which prioritizes nodes based on a heuristic, and Dijkstra's algorithm, which ensures the shortest path. This combination allows A* to efficiently find the optimal path by considering both the heuristic information and the actual cost of reaching the node.