Data Structures and Algorithm Analysis Quiz

The different searching techniques include Linear search, Binary search, and Indexed search. Linear search involves iterating through each element in a list until the target element is found. Binary search works on the principle of divide and conquer, where the list is repeatedly divided in half until the target element is found. Indexed search involves using an index to directly access the elements in a data structure such as an array.

Big Oh notation, denoted as $O(f(n))$, represents the upper bound of an algorithm's time complexity. Theta notation, denoted as $\Theta(f(n))$, represents the average case time complexity of an algorithm. Omega notation, denoted as $\Omega(f(n))$, represents the lower bound of an algorithm's time complexity. These notations help in analyzing and comparing the efficiency of different algorithms in terms of time and space usage.

Bubble Sort repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order. Merge Sort uses the divide and conquer approach to recursively divide the list into smaller sublists, sort them, and then merge them back together. Quick Sort also uses the divide and conquer approach and selects a 'pivot' element to partition the list into smaller elements less than the pivot and larger elements greater than the pivot.