Can you explain the concept of lossless and lossy compression in the context of string compression algorithms?
- Lossless compression discards some data during compression but can fully recover the original data during decompression.
- Lossless compression retains all original data during compression and decompression.
- Lossy compression intentionally discards some data during compression, and the lost data cannot be fully recovered during decompression.
- Lossy compression retains all original data during compression but sacrifices some data during decompression.
In the context of string compression algorithms, lossless compression retains all original data during compression and decompression. On the other hand, lossy compression intentionally discards some data during compression, and the lost data cannot be fully recovered during decompression. The choice between lossless and lossy compression depends on the application's requirements and the acceptable level of data loss.
What does topological sorting primarily aim to do in a directed graph?
- Arranges the vertices in a linear order such that for every directed edge (u, v), vertex u comes before vertex v in the order.
- Finds the shortest path between two vertices in the graph.
- Identifies cycles in the graph.
- Rearranges the vertices randomly.
Topological sorting in a directed graph aims to arrange the vertices in a linear order such that for every directed edge (u, v), vertex u comes before vertex v in the order. This order is often used to represent dependencies between tasks or events.
Discuss the space complexity of merge sort and how it compares to other sorting algorithms.
- O(log n)
- O(n log n)
- O(n)
- O(n^2)
Merge sort has a space complexity of O(n) due to its need for additional memory. This is more efficient than algorithms with higher space complexity, like quicksort with O(n^2) in the worst case, making merge sort advantageous in terms of space usage.
Selection sort is not suitable for _______ datasets as it performs a fixed number of comparisons and swaps.
- Large
- Randomized
- Small
- Sorted
Selection sort is not suitable for large datasets as it performs a fixed number of comparisons and swaps. Regardless of the input, it always performs the same number of operations, making it inefficient for large datasets.
You're developing software for a ride-sharing service. How might you use a queue to handle incoming ride requests and allocate drivers to passengers?
- Allocate drivers based on a first-come, first-served basis from the queue.
- Assign drivers based on random selection for variety.
- Implement a queue where the longest waiting driver is assigned to the next ride.
- Use a priority queue to allocate drivers based on passenger ratings.
In a ride-sharing service, using a queue for driver allocation involves assigning drivers on a first-come, first-served basis from the queue. This ensures fairness and efficiency in handling incoming ride requests.
BFS, nodes are visited level by level, starting from the _______ node.
- Intermediate
- Leaf
- Random
- Root
In BFS (Breadth-First Search), nodes are visited level by level, starting from the root node. The algorithm explores all nodes at the current level before moving to the next level.
Associativity plays a key role in optimizing Matrix Chain Multiplication by _______.
- Allowing reordering of matrix multiplication operations
- Ensuring the matrices are square matrices
- Ignoring the order of matrix multiplication
- Restricting the order of matrix multiplication
Associativity plays a key role in optimizing Matrix Chain Multiplication by allowing the reordering of matrix multiplication operations. This flexibility enables the algorithm to find the most efficient sequence of multiplications.
In the context of the Longest Increasing Subsequence problem, "increasing" refers to the sequence where each element is _______ than the previous one.
- Divisible
- Equal
- Larger
- Smaller
In the context of the Longest Increasing Subsequence problem, "increasing" refers to the sequence where each element is Larger than the previous one. The goal is to find the longest subsequence where each element is strictly increasing.
Breadth-First Search (BFS) is commonly used in _______ for finding the shortest path between two nodes.
- Game Development
- Image Processing
- Network Routing
- Sorting Algorithms
Breadth-First Search (BFS) is commonly used in network routing for finding the shortest path between two nodes. It explores nodes level by level, making it efficient for finding the shortest path in networks.
In the Knapsack Problem, what are the typical constraints that need to be considered?
- Height and Depth
- Length and Width
- Volume and Size
- Weight and Value
The typical constraints in the Knapsack Problem include the weight and value of the items. These constraints ensure that the selected items do not exceed the capacity of the knapsack while maximizing the total value.