Stacks are commonly used in _______ processing, where the last operation performed needs to be reversed first.
- Batch
- Parallel
- Redo
- Undo
Stacks are commonly used in Undo processing, where the last operation performed needs to be reversed first. The Last-In-First-Out (LIFO) nature of stacks makes them suitable for managing such sequential operations.
Can bubble sort be used efficiently for sorting large datasets? Why or why not?
- It depends on the distribution of elements in the dataset
- No, it has a time complexity of O(n^2), making it inefficient for large datasets
- Only for datasets with a prime number of elements
- Yes, it has a linear time complexity for large datasets
Bubble sort is not efficient for sorting large datasets due to its time complexity of O(n^2). The algorithm involves nested loops, making the number of comparisons and swaps increase quadratically with the size of the dataset, leading to poor performance for large datasets.
What is the time complexity of searching for an element in a balanced binary search tree like AVL or red-black tree?
- O(1)
- O(log n)
- O(n log n)
- O(n)
The time complexity of searching for an element in a balanced binary search tree, such as AVL or red-black tree, is O(log n), where 'n' is the number of elements in the tree. The balanced structure allows for efficient search operations, maintaining logarithmic time complexity.
A _______ is a data structure that allows elements to be inserted from one end and removed from the other end.
- Deque
- Linked List
- Queue
- Stack
A deque (double-ended queue) is a data structure that allows elements to be inserted from one end and removed from the other end. This provides flexibility in adding and removing elements from both the front and rear, making it a versatile data structure.
What is the time complexity of radix sort?
- O(d * (n + b))
- O(log n)
- O(n log n)
- O(n^2)
The time complexity of radix sort is O(d * (n + b)), where 'd' is the number of digits in the input numbers, 'n' is the number of elements, and 'b' is the base of the numeric representation.
Linear search examines each element in the array _______ until the desired element is found or the end of the array is reached.
- None of the above
- One by one
- Randomly
- Skip a few at a time
Linear search examines each element in the array one by one until the desired element is found or the end of the array is reached. It starts from the beginning and checks each element sequentially.
Selecting a _______ pivot element in Quick Sort can significantly reduce its time complexity.
- Largest
- Middle
- Random
- Smallest
Selecting a random pivot element in Quick Sort can significantly reduce its time complexity by minimizing the chance of encountering the worst-case scenario, leading to more balanced partitions.
One of the key advantages of merge sort is its _______ time complexity in all cases.
- O(log n)
- O(n log n)
- O(n)
- O(n^2)
One of the key advantages of merge sort is its O(n log n) time complexity in all cases. This makes it more efficient than some other sorting algorithms, especially in scenarios with large datasets.
Suppose you're designing a software tool for identifying similar images. Discuss how you would adapt algorithms for the longest common substring problem to compare image data and find common features.
- By comparing the image sizes without analyzing the actual content.
- By converting image data into a format suitable for string comparison and applying longest common substring algorithms.
- By focusing only on the overall color distribution in the images.
- By randomly selecting pixels in the images for substring comparison.
Adapting longest common substring algorithms for image comparison involves converting image data into a format suitable for string comparison. This allows for the identification of common features by analyzing substrings within the image data.
How does topological sorting differ from other sorting algorithms like bubble sort or merge sort?
- Topological sorting has a time complexity of O(n^2), whereas bubble sort and merge sort have better time complexities of O(n^2) and O(n log n) respectively.
- Topological sorting is a comparison-based sorting algorithm, similar to bubble sort and merge sort.
- Topological sorting is an in-place sorting algorithm, whereas bubble sort and merge sort require additional space for sorting.
- Topological sorting is specifically designed for directed acyclic graphs (DAGs) and maintains the order of dependencies, while bubble sort and merge sort are general-purpose sorting algorithms for arrays.
Topological sorting is specialized for directed acyclic graphs (DAGs), ensuring a valid sequence of dependencies, unlike general-purpose sorting algorithms such as bubble sort and merge sort.