What problem-solving technique is commonly used in traversal algorithms?

Traversal algorithms typically involve systematically visiting each node or element in a data structure, such as a tree or a graph. The most common techniques employed in traversal are iteration and recursion.

Using iteration, you may implement loops to visit each element successively. This is straightforward and effectively handles many traversal scenarios. For example, in a breadth-first search (BFS) on a graph, an iterative approach using a queue is commonly utilized to explore nodes layer by layer.

Recursion, on the other hand, is particularly convenient for traversing data structures like trees, where each subtree can be treated as a smaller instance of the same problem. In a depth-first search (DFS) on trees, recursive calls allow easy backtracking to explore each branch thoroughly before moving on to subsequent branches.

Thus, both iteration and recursion are fundamental to effectively visiting all parts of the data structure during traversal, making this choice the correct answer.