Depth-First Search Questions at Zenefits: What to Expect

Depth-First Search (DFS) is a core algorithm for navigating tree and graph structures, making it essential for solving problems related to hierarchies, paths, and connected components. At Zenefits, which builds HR, payroll, and benefits software, these structures model real-world data like company reporting chains, dependency graphs for compliance rules, or permission hierarchies. Their interview question bank includes three specific DFS problems, indicating they test for this fundamental skill to assess your ability to handle recursive exploration and backtracking—key for feature development and data processing at scale.

What to Expect — Types of Problems

Zenefits' DFS questions typically fall into two categories. The first is Tree Traversal and Manipulation. Expect problems involving binary trees or n-ary trees where you must search for nodes, validate properties, or compute values (like maximum depth or path sums). These mirror operations on organizational charts or policy rule trees. The second category is Graph Search and Path Finding. Here, you'll work with implicit or explicit graphs to find connected components, detect cycles, or explore all possible states (like in a backtracking scenario). This pattern is crucial for features like mapping employee permissions across interconnected systems. Problems often require iterative or recursive solutions with careful state management to avoid infinite loops.

How to Prepare — Study Tips with One Code Example

Master the recursive template for DFS and its iterative stack-based variant. Practice identifying base cases and visited state tracking for graphs. A key pattern is the pre-order traversal for tree paths, used in many problems. Below is a standard DFS template to find all root-to-leaf paths in a binary tree.

def binary_tree_paths(root):
    def dfs(node, path):
        if not node:
            return
        path.append(str(node.val))
        if not node.left and not node.right:
            paths.append("->".join(path))
        else:
            dfs(node.left, path)
            dfs(node.right, path)
        path.pop()

    paths = []
    dfs(root, [])
    return paths

Recommended Practice Order

Start with basic tree traversals (pre-order, in-order, post-order) to build recursion intuition. Move to classic problems like maximum depth, path sum, and subtree validation. Then tackle graph DFS on adjacency lists for cycle detection and connected components. Finally, practice backtracking problems (e.g., permutations, subsets) which use DFS to explore decision trees. Always analyze time and space complexity, as Zenefits evaluates scalable solutions.

Practice Depth-First Search at Zenefits