Depth-First Search Questions at DoorDash: What to Expect

Depth-First Search (DFS) is a fundamental algorithm for exploring graphs and trees, making it essential for solving problems involving hierarchical data, paths, and connected components. At DoorDash, where engineers build systems for mapping, logistics, order dispatching, and menu categorization, DFS is a practical tool for real-world scenarios like route exploration, dependency resolution, or parsing nested data structures. With 17 out of 87 total coding questions tagged with DFS, it's a pattern you cannot afford to overlook.

What to Expect — Types of Problems

DoorDash’s DFS questions typically fall into three categories. First, tree and binary tree problems, such as calculating path sums, finding ancestors, or serializing tree structures, which model hierarchical data like restaurant menus or delivery zones. Second, graph traversal and pathfinding problems, where you might need to check connectivity between nodes, find all paths from a start to an end point, or detect cycles—directly applicable to mapping and network analysis. Third, matrix/grid traversal problems, like counting islands or finding exit paths in a maze, which can represent delivery maps or warehouse layouts. Expect variations that combine DFS with other concepts, such as backtracking for generating permutations or memoization for optimization.

How to Prepare — Study Tips with One Code Example

Master both recursive and iterative (stack-based) implementations of DFS. Understand pre-order, in-order, and post-order traversals for trees. Practice identifying when a problem is inherently a graph traversal—look for keywords like “find all possible paths,” “connected components,” or “explore all options.” Always clarify input constraints to avoid stack overflow in recursion. For preparation, solve problems on binary tree DFS, graph cycle detection, and grid search.

A key pattern is using DFS to traverse all nodes in a binary tree, collecting values. Here’s a standard recursive implementation in three languages:

def dfs_tree_traversal(root):
    result = []
    def dfs(node):
        if not node:
            return
        # Pre-order: process node before children
        result.append(node.val)
        dfs(node.left)
        dfs(node.right)
    dfs(root)
    return result

Recommended Practice Order

Start with basic tree traversals to build intuition. Move to path-sum problems and finding nodes in a tree. Then, tackle graph DFS on adjacency lists, focusing on cycle detection and connected components. Progress to matrix DFS problems like “number of islands.” Finally, combine DFS with backtracking for permutation/combination questions. Time yourself to simulate interview conditions.

Practice Depth-First Search at DoorDash