What is the difference between DFS and BFS?
This question evaluates your ability to clearly explain the differences between two search strategies, focusing on the order of exploration, performance characteristics, and practical use cases rather than just definitions.
It’s important to illustrate when each algorithm is more appropriate depending on the problem context.
Answer 1: Use-case focused explanation
English
DFS is often better when you need to explore all possible paths
or detect cycles
in a graph. It goes deep into one branch before backtracking. In contrast, BFS is more suitable when you’re looking for the shortest path in an unweighted graph
, since it explores nodes level by level.
For example, if you're solving a maze and need the shortest way out
, BFS is the better option. But if you’re trying to analyze all possible outcomes
or find any valid path
, DFS works well.
Key Expressions
- explore all possible paths: investigate all possible routes
- detect cycles: find if a loop exists in a graph
- shortest path in an unweighted graph: minimum number of steps in a graph with no edge weights
- analyze all possible outcomes: examine every possible result
- find any valid path: discover at least one successful route
Answer 2: Spoken-form with contrasting goals
English
The main difference comes down to the kind of problem you're trying to solve. DFS is helpful when the goal is to go deep
and explore the full structure
, especially when you’re looking for any solution. On the other hand, BFS is better when you need the quickest path
to a target, particularly when all edges have equal weight.
For example, in a game where you're looking for any winning strategy
, DFS might make more sense. But if you want the fastest way to reach a goal
, such as in network routing
or map navigation
, BFS is usually the better fit.
Key Expressions
- go deep: follow a path down to its end before backtracking
- explore the full structure: examine every branch or node
- quickest path: the most efficient or shortest route
- any winning strategy: a valid solution, regardless of efficiency
- network routing / map navigation: common BFS use cases for finding optimal paths
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