If you have an array of size 5 and you try to add a 6th element to it, what is a likely outcome?
An error or exception will occur indicating an out-of-bounds access.
The new element will overwrite the value at the first index (index 0).
The array will automatically resize to accommodate the new element.
The behavior is undefined and can lead to unpredictable program crashes.
You need to search for an element in an array where elements are randomly placed. Which search algorithm is your only option?
Both can be used effectively.
Linear Search
None of the above.
Binary Search
Which of the following sorting algorithms has the best average-case time complexity?
Bubble Sort
Merge Sort
Insertion Sort
Selection Sort
Which sorting algorithm works by repeatedly selecting the minimum element and placing it in its correct position?
Quick Sort
Given an array of integers, how can you efficiently count the occurrences of a specific element?
Iterate through the array and increment a counter for each occurrence.
Use a hash map to store the frequency of each element.
All of the above methods are equally efficient.
Sort the array and use binary search.
What is the main disadvantage of using bubble sort for large datasets?
It cannot handle duplicate values.
It has a high time complexity, making it inefficient.
It requires additional memory space.
It is difficult to implement.
What is a key difference between a 1D array and a 2D array?
1D arrays are static in size, 2D arrays can change size dynamically.
1D arrays can only be accessed sequentially, 2D arrays allow random access.
1D arrays store numbers while 2D arrays store characters.
1D arrays represent linear sequences, 2D arrays represent tabular data.
Which of the following is a valid array declaration in a common programming language (syntax may vary slightly)?
array numbers = [1, 2, 3, 4];
All of the above.
numbers = array(1, 2, 3, 4);
int numbers[] = {1, 2, 3, 4};
What is the time complexity of finding the maximum element in a sorted array?
O(log n)
O(1)
O(n)
O(n log n)
What is the time complexity of accessing an element in a 2D array with 'm' rows and 'n' columns?
O(m + n)
O(m * n)
O(log m + log n)