The time complexity of the standard dynamic programming approach for Matrix Chain Multiplication is _______.
- O(2^n)
- O(n)
- O(n^2)
- O(n^3)
The time complexity of the standard dynamic programming approach for Matrix Chain Multiplication is O(n^3), where 'n' is the number of matrices being multiplied. This is achieved through a bottom-up dynamic programming approach that efficiently calculates the optimal parenthesization.
What does Longest Increasing Subsequence (LIS) refer to?
- The longest subarray with elements in non-decreasing order.
- The longest subarray with elements in strictly increasing order.
- The maximum sum of elements in a subarray with consecutive elements.
- The minimum sum of elements in a subarray with consecutive elements.
Longest Increasing Subsequence (LIS) refers to the longest subarray with elements in strictly increasing order. The goal is to find the length of this subsequence.
What is the primary goal of solving the Longest Palindromic Substring problem?
- Checking if a string is entirely composed of unique characters.
- Counting the total number of palindromes in a given string.
- Identifying the longest substring that is a palindrome within a given string.
- Rearranging the characters in a string to form a palindrome.
The primary goal of solving the Longest Palindromic Substring problem is to identify the longest substring within a given string that reads the same backward as forward, i.e., a palindrome.
What is the primary objective of the A* search algorithm?
- Explore all nodes in a random order
- Find the shortest path from the start node to the goal node
- Skip nodes with high heuristic values
- Sort nodes based on their values
The primary objective of the A* search algorithm is to find the shortest path from the start node to the goal node by considering both the cost to reach the node and a heuristic estimate of the remaining cost.
The _______ algorithm is commonly used for lossless compression in string compression techniques.
- Bubble
- Huffman
- Merge
- Quick
The Huffman algorithm is commonly used for lossless compression in string compression techniques. It is a variable-length coding algorithm that assigns shorter codes to more frequent characters, optimizing the compression process.
How does the brute-force approach to finding the Longest Palindromic Substring work?
- It employs a divide-and-conquer strategy to find palindromic substrings.
- It sorts the characters in the string and identifies the longest sorted palindrome.
- It systematically checks all possible substrings and identifies the longest palindrome.
- It utilizes a hash table to store palindrome information for quick retrieval.
The brute-force approach to finding the Longest Palindromic Substring works by systematically checking all possible substrings of the given string and identifying the longest palindrome among them. This method has a quadratic time complexity.
You're designing a course curriculum where certain courses have prerequisites. How would you use topological sorting to organize the courses in a way that ensures students take prerequisite courses before advanced ones?
- Alphabetically arrange the courses.
- Arrange courses based on their popularity.
- Randomly select courses for scheduling.
- Use topological sorting to schedule courses based on prerequisites, ensuring prerequisite courses are taken before the advanced ones.
Topological sorting is applied to schedule courses in a curriculum with prerequisites. It guarantees that prerequisite courses are scheduled before any course that depends on them, ensuring students take foundational courses before advanced ones.
Binary search can lead to _______ when applied to non-sorted arrays, yielding incorrect results or infinite loops.
- Linear
- Optimal
- Quadratic
- Unpredictable
Binary search can lead to unpredictable behavior when applied to non-sorted arrays. Without the assurance of sorted elements, the algorithm may yield incorrect results or even result in infinite loops.
What happens when you try to remove an element from an empty queue?
- Exception is raised
- Nothing, the operation is silently ignored
- Program crashes
- The last element is removed
When attempting to remove an element from an empty queue, the operation is usually silently ignored. This is because there are no elements in the queue, and there is nothing to remove.
How does the Last In, First Out (LIFO) principle apply to stacks?
- Elements are removed in a random order.
- Elements are removed in ascending order.
- The first element added is the first one to be removed.
- The last element added is the first one to be removed.
The Last In, First Out (LIFO) principle in stacks means that the last element added is the first one to be removed. This principle is essential for operations like push (adding an element to the stack) and pop (removing the last added element).