Recursion

The range within which to search is halved.

The entire collection gets sorted again before searching continues.

All elements in the collection are compared with the target again.

An element is added to the collection being searched through.

$O(\log n)$

$O(1)$

$O(n)$

$O(n \log n)$

It begins comparing each pair of adjacent elements within a single array pass.

It performs an insertion sort on small arrays for efficiency improvement.

It switches from recursive calls to iterative processing of data subsets.

It stops dividing arrays because it has reached an array size of one or zero elements.

To split the array into smaller subarrays for recursion.

To determine the position of the middle element of an array

To identify if the array is already sorted and skip the recursion.

To compare and merge the subarrays to produce a sorted array.

The binary search will repeatedly halve the search interval until it determines the target value is not present.

The binary search algorithm will loop infinitely because it expects to find every searched value.

The binary search will modify the array by sorting it again before concluding that the target is missing.

The binary search will continue to search until it reaches the end of the array and return -1.

Bubble sort followed by linear search.

Linear search.

Binary search.

Selection sort followed by binary search.

Setter Method

Constructor

Object Function

Initializer Block

Selection sort

Merge sort

Linear search

Insertion sort

Potentially deeper recursion due decreased node fill-rate prior balancing adjustments.

Faster insertions overall owing parallelizable nature quartile divisions.

Increased memory usage due requiring additional pointers per node.

Reduced recursion depth increased branching factor leads higher efficiency.

Equal to the height plus one.

Once per level traversed.

For each node in the entire structure.

Twice the total number of nodes.