The A* search algorithm uses a _______ function to estimate the cost of reaching the goal from a given state.
- Admissible
- Cost
- Heuristic
- Informed
A* utilizes a heuristic function to estimate the cost of reaching the goal from a given state. This heuristic guides the search by providing an informed guess about the remaining cost, helping A* prioritize paths likely to lead to the optimal solution efficiently.
Merge sort demonstrates _______ behavior, making it a suitable choice for sorting large datasets.
- Backtracking
- Divide-and-conquer
- Dynamic programming
- Greedy
Merge sort demonstrates divide-and-conquer behavior, as it recursively breaks down the sorting problem into smaller sub-problems, making it efficient for handling large datasets.
How is the coin change problem related to dynamic programming?
- Dynamic programming is employed to solve subproblems efficiently and avoid redundant calculations.
- Dynamic programming is only applicable to certain variations of the problem.
- Dynamic programming is used to count the total number of coins, but not for optimization.
- It isn't related to dynamic programming.
The coin change problem is related to dynamic programming as it involves solving subproblems efficiently and storing their solutions to avoid redundant calculations. Dynamic programming is used to find the optimal combination of coins to minimize the total count.
Describe the process of sorting an array using Insertion Sort step by step.
- Build the sorted array one element at a time
- Divide the array into subarrays for sorting
- Multiply each element by a random factor
- Swap elements until the smallest is at the end
The Insertion Sort process involves building the sorted array one element at a time. Each iteration takes an element from the unsorted part and inserts it into its correct position in the sorted part, shifting other elements accordingly.
The in-place nature of Insertion Sort makes it suitable for sorting _______ data structures.
- Hash Tables
- Linked Lists
- Priority Queues
- Trees
The in-place nature of Insertion Sort makes it suitable for sorting linked lists. Since it only requires constant extra memory space, it's advantageous for scenarios where memory allocation is a concern.
The Fibonacci sequence is defined by the recurrence relation F(n) = F(n-1) + F(n-2), where F(n) represents the _______ Fibonacci number.
- 1st
- 2nd
- 3rd
- 4th
In the recurrence relation F(n) = F(n-1) + F(n-2), F(n) represents the (n)th Fibonacci number, the sum of the two preceding numbers in the sequence. So, it represents the 2nd Fibonacci number in this context.
How does the concept of recursion relate to the implementation of binary search?
- Recursion involves breaking a problem into subproblems and solving them. Binary search naturally lends itself to recursion because it repeatedly solves a smaller instance of the same problem.
- Recursion is not applicable to binary search
- Recursion is only used in iterative algorithms
- Recursion is used in sorting algorithms
The concept of recursion aligns well with binary search. The algorithm repeatedly divides the array into halves, creating a recursive structure. Each recursive call works on a smaller portion of the array until the target is found or the base case is met.
What does regular expression matching involve?
- Identifying the smallest element in a collection.
- Matching patterns in text using a sequence of characters and metacharacters.
- Randomly rearranging elements for pattern recognition.
- Sorting elements in a list based on a predefined order.
Regular expression matching involves identifying patterns in text using a sequence of characters and metacharacters. These patterns can represent specific sequences, characters, or conditions, enabling powerful text searching and manipulation.
What data structure is commonly used in BFS to keep track of visited vertices?
- Array
- Linked List
- Queue
- Stack
A queue is commonly used in BFS to keep track of visited vertices. The queue follows the First In First Out (FIFO) principle, ensuring that vertices are processed in the order they are discovered.
Dijkstra's algorithm is more efficient than _______ for finding the shortest path from a single source vertex to all other vertices in a graph with non-negative edge weights.
- Bellman-Ford algorithm
- Depth-First Search
- Kruskal's algorithm
- Prim's algorithm
Dijkstra's algorithm is more efficient than Bellman-Ford algorithm for finding the shortest path in a graph with non-negative edge weights. Dijkstra's algorithm has a time complexity of O((V + E) log V), where V is the number of vertices and E is the number of edges.