Depth-First Search Questions at PhonePe: 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, connected components, and pathfinding. At PhonePe, a leading fintech platform handling payments, financial data, and complex transaction graphs, these are daily realities. Their technical interviews reflect this: 14 of their 102 cataloged coding questions explicitly involve DFS. Mastering it demonstrates your ability to navigate interconnected data structures, a core skill for building scalable and reliable financial systems.

What to Expect — Types of Problems

PhonePe's DFS questions typically fall into three categories, moving from foundational to complex.

Tree Traversal & Manipulation: Expect problems on binary trees, such as finding the maximum depth, checking if a tree is symmetric, or serializing/deserializing its structure. These test your understanding of recursive exploration and tree properties.

Graph Connectivity & Cycles: Given PhonePe's network of users and transactions, you'll encounter problems to find connected components in an undirected graph, detect cycles, or determine if a path exists between nodes. These questions assess your ability to model real-world relationships.

Pathfinding & Backtracking: More advanced problems involve finding specific paths, sequences, or combinations. Examples include finding all paths in a tree that sum to a target value (relevant for transaction analysis) or generating all possible permutations. These combine DFS with state management and pruning.

The progression often starts with a straightforward tree traversal and can escalate to a backtracking scenario on a 2D grid or a complex graph.

How to Prepare — Study Tips with Code Example

Focus on internalizing the recursive and iterative implementations of DFS. For trees, practice pre-order, in-order, and post-order traversals. For graphs, ensure you can handle both adjacency lists and matrices, and remember to track visited nodes to avoid infinite loops.

A key pattern is the recursive DFS skeleton for traversing a binary tree. This pattern is the foundation for almost all tree-based DFS problems.

def dfs(node):
    if not node:
        return
    # Pre-order processing: do something with node.val here
    dfs(node.left)
    # In-order processing (for BST)
    dfs(node.right)
    # Post-order processing

To solve a problem, you insert the specific logic—like comparing values, summing paths, or collecting nodes—into the appropriate processing stage. For graph DFS, the structure is similar but uses a visited set and iterates over neighbors.

Recommended Practice Order

Build competence systematically. Start with basic tree traversals to build muscle memory. Next, solve problems on tree properties (height, symmetry). Then, move to graph fundamentals: finding connected components and cycle detection. Finally, tackle backtracking and pathfinding problems, which are the most common in PhonePe's harder interviews. Always analyze the time and space complexity of your solution, as interviewers will expect it.

Practice Depth-First Search at PhonePe