DFS is particularly useful for cycle detection in a graph as it can track visited nodes and backtrack effectively.

BFS is commonly used in broadcasting scenarios where messages need to be sent to all nodes in a network efficiently.

The main advantage of BFS is that it guarantees the shortest path in unweighted graphs by exploring all nodes at the present depth before moving deeper.

BFS is primarily used for finding the shortest path in an unweighted graph because it explores all neighbors at the present depth prior to moving on to nodes at the next depth level.

The time complexity of BFS is O(V + E) because it visits each vertex and edge once.

DFS is typically used for topological sorting of a directed acyclic graph (DAG) because it can explore all paths and backtrack effectively.

DFS is commonly used in web crawling to explore the links on a webpage deeply before backtracking to explore other links.

DFS explores as far as possible along each branch before backtracking, which means it does not explore all neighbors before going deeper.

DFS is typically used to find all possible paths in a maze as it explores each path deeply before backtracking.