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## Which Of The Following Algorithm Traversal Requires More Memory

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## Which Of The Following Algorithm Traversal Requires More Memory

In computing, an algorithm is a step-by-step procedure for solving a problem. Algorithm traversal is the process of visiting each node of a tree or graph one after the other, and selecting the best solution from among the possibilities at each node. Each node in the tree or graph corresponds to a particular execution of the algorithm. For example, if we are trying to find the largest number in an array, we would start at the root of the tree and work our way down to find the largest value. Depending on the size and complexity of your data structure, you may need more memory to execute an algorithm than just RAM. In this blog post, we will explore which algorithm requires more memory and why.

## Binary Search

In computer science, a binary search algorithm is a search algorithm that uses two data structures, the left-most and the right-most elements of which are compared to find an item. This algorithm generally requires less memory than other algorithms because it can use pointers instead of arrays.

## Selection Sort

The algorithm selection sort, which is a quick sort, requires less memory than the bubble sort. The bubble sort stores the smaller numbers in a stack and pops them as they are needed, while the selection sort keeps all of the numbers in a list and selects the smallest one.

## Quicksort

When sorting a list of objects, the algorithm called quicksort is generally faster than the algorithm called merge sort. Merge sort compares neighboring objects and swaps them if they are not equal. Quicksort does not need to compare neighboring objects, but instead uses a heuristic to determine where the sorted list should go next.

Since quicksort requires less memory to run than merge sort, it will be faster for smaller lists. However, on larger lists quicksort may actually require more memory because it has to keep track of the position of each object in the sorted list.

## Comparison of Algorithm Traversal Methods

There are a few different algorithm traversal methods that can be used to find a requested element in an array or list. Each method has its own benefits and drawbacks, so it is important to choose the one that is best suited for the task at hand. The three most common methods are breadth-first search, depth-first search, and sequential search.

Each of these methods has its own advantages and disadvantages. BFS is the quickest of the three, but it can require more memory than the other two methods. DFS is slower than BFS, but requires less memory. Sequential search is the slowest of the three, but it can return results in reverse order if necessary.

It is important to choose an algorithm based on the task at hand and the resources available. If memory is scarce, BFS should be used instead of DFS; if speed is a priority, sequential search should be chosen over DFS; and if memory or speed aren’t concerns, then BFS or DFS can both be used without penalty.