Given an array of integers, find the subarray with the maximum sum in linear time. The subarray must contain at least one element.
Dynamic programming approach by building a table to store the maximum sum ending at each index.
Brute force approach by checking all possible subarrays.
Divide and conquer approach by finding the maximum subarray in the left half, right half, and the one crossing the midpoint.
Kadane's Algorithm, which iterates through the array, keeping track of the maximum sum ending at each index.
You are designing a dynamic array implementation that needs to support efficient insertion at both the beginning and the end. Which of the following underlying data structures would be the MOST suitable to achieve this with optimal time complexity?
Singly Linked List
Binary Search Tree
Doubly Linked List
Circular Buffer
You are given an array of integers nums and an integer k. Find the total number of continuous subarrays whose sum equals to k.
Use two nested loops to iterate through all possible subarrays.
Use a sliding window approach to find subarrays with the given sum.
Use dynamic programming to store the number of subarrays with sum k ending at each index.
Use a hash table to store the cumulative sum of elements and their frequency.
In a real-world application, you are using a dynamic array to store a constantly growing dataset. You notice that the performance degrades significantly during the array resizing operations. What strategy could you employ to mitigate this performance bottleneck?
Increase the frequency of resizing, reallocating the array with smaller size increments.
Implement a custom memory allocator that reserves larger chunks of contiguous memory in advance.
Optimize the algorithm that processes the data to reduce the overall number of insertions into the array.
Switch to a linked list data structure, sacrificing some element access speed for better insertion performance.
Given an array of n positive integers and a positive integer s, find the minimal length of a contiguous subarray of which the sum ≥ s. If there isn't one, return 0 instead.
Use a sliding window approach to find the minimal length subarray.
Use dynamic programming to store the minimal length for all subarrays ending at each index.
Use binary search to find the minimal length.
What is a significant disadvantage of using arrays for storing and processing extremely large datasets, particularly in the context of limited memory resources?
Arrays do not support dynamic resizing, making it challenging to handle growing datasets.
Arrays require contiguous blocks of memory, which can be difficult to allocate for massive datasets.
Arrays have slow access times for individual elements.
Arrays are not suitable for storing structured data, such as key-value pairs.
Which sorting algorithm is the MOST suitable for sorting a massive dataset that cannot fit entirely in RAM?
Quick Sort
Merge Sort
External Merge Sort
Bubble Sort
Which of the following array operations has an average-case time complexity that differs from its worst-case time complexity?
Inserting an element at the beginning of a dynamic array (implemented with reallocation).
Searching for a specific value in a sorted array.
Deleting an element from the end of an array.
Accessing an element at a given index.
Which data structure would be the MOST suitable for implementing a sparse matrix efficiently, where most elements are zero, to save memory and potentially improve computation speed?
Hash Table
Multidimensional Array
Linked List
Binary Tree
You are given an unsorted array of integers where each element represents the height of a bar in a histogram. Find the largest rectangular area in the histogram.
Sort the array and calculate the area for each subarray.
Iterate through the array and maintain a stack to track potential rectangle heights.
Use dynamic programming to store the maximum area ending at each index.
Use a divide and conquer approach to find the minimum element in each subarray.