What is a key difference between Depth$-$First Search $($DFS$)$ and Breadth$-$First Search $($BFS$)$ in graph traversal?

DFS explores as far as possible along each branch before backtracking, while BFS explores all the neighbors of a vertex before moving to the next level.

While DFS is adept at exploring all possible paths and is often used for pathfinding and backtracking algorithms, BFS is uniquely suited for finding the shortest path in unweighted graphs, due to its systematic level$-$by$-$level exploration.

BFS is often implemented using iterative approaches with a queue to ensure level$-$by$-$level traversal, in contrast to DFS which leverages recursion or a stack to delve deep into each possible path before exploring alternatives.

DFS typically requires more memory than BFS$,$ especially in densely connected graphs, as it needs to maintain a stack for the vertices explored along the path, unlike BFS which systematically explores vertex levels.