What characterizes Depth-First Search (DFS)?

Depth-First Search (DFS) is characterized by its approach of exploring the most promising paths as deeply as possible before backtracking. This technique enables it to dive deep into the tree or graph structure, exploring one branch as far as it can go until it encounters a dead end. At that point, it backtracks to the last decision point and explores the next branch. This method of exploration allows DFS to efficiently traverse deep and lengthy paths, which is particularly useful when searching for solutions or paths in complex structures.

The essence of DFS is captured in the ability to commit to a path and explore it until no further nodes can be visited, at which point it retreats and tests alternative routes. This depth-focused strategy distinguishes DFS from breadth-first approaches that explore neighbors in broad layers. Understanding this core characteristic helps clarify how DFS operates effectively in various applications, such as puzzle solving or searching through unstructured data.