None of these

By checking the middle element of the array

By dividing the array into fixed-size chunks

By using a binary division regardless of data distribution

By estimating the likely position using the key’s value relative to the range of the array

By recursively comparing the key with each element from start to end

Insertion Sort always outperforms Quick Sort on large datasets.

Insertion Sort is not suitable for nearly sorted data.

Insertion Sort requires additional memory proportional to input size.

Insertion Sort has a worst-case time complexity of O(n log n).

Insertion Sort is a stable and in-place sorting algorithm.

None of these

To evaluate whether a path from i to j can be shortened via k

To reduce the number of edges adjacent to vertex k in the graph

To prioritize vertices with higher degrees during path updates for each intermediate vertex k

To remove all self-loops from the graph going through vertex k

To detect cycles in the graph including vertex k

Items have fractional weights

None of these

All items have the same value and weight

All item values are zero

Knapsack capacity is very large

The item with the best value/weight ratio cannot be combined with others due to its weight

O(n+m)

O(m)

O(mn)

O(n+mᐧ|Σ|)

O(mᐧ|Σ|)

[27, 38, 3, 43, 9, 82, 10, 11]

[27, 38, 3, 43, 9, 10, 82, 11]

[27, 38, 43, 3, 9, 10, 11, 82]

[27, 38, 3, 43, 10, 82, 9, 11]

[3, 27, 38, 9, 10, 11, 43, 82]