Different searching and sorting algorithms in C$++$ can vary in terms of efficiency, speed, and practical applications.

For searching algorithms:

Linear Search:

Efficiency: O$($n$)$ where n is the number of elements in the array.

Speed: Slower for large datasets.

Practical Applications: Suitable for small datasets or unsorted arrays.

Binary Search:

Efficiency: O$($log n$)$ where n is the number of elements in the array.

Speed: Faster for sorted arrays.

Practical Applications: Ideal for large datasets and sorted arrays.

For sorting algorithms:

Bubble Sort:

Efficiency: O$($n$^2)$ in the worst case.

Speed: Slower for large datasets.

Practical Applications: Simple implementation but not efficient for large datasets.

Quick Sort:

Efficiency: O$($n log n$)$ on average.

Speed: Faster for large datasets.

Practical Applications: Efficient for large datasets and widely used in practice.

Merge Sort:

Efficiency: O$($n log n$)$ in all cases.

Speed: Consistently fast.

Practical Applications: Stable sorting algorithm suitable for large datasets.

In conclusion, the choice of searching and sorting algorithms in C$++$ depends on the size of the dataset, whether it is sorted or unsorted, and the specific requirements of the application. Each algorithm has its own strengths and weaknesses, so it is important to select the most appropriate one based on the specific scenario.