Depth-First Search Questions at eBay: 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 eBay, where engineers manage complex systems like user networks, product catalogs, and recommendation engines, DFS is a practical tool for traversing dependencies and relationships. With 10 out of 60 total coding questions at eBay focused on DFS, mastering it is non-negotiable for interview success. It tests your ability to handle recursive thinking, backtracking, and systematic exploration—skills directly applicable to eBay's large-scale, data-driven platforms.

What to Expect — Types of Problems

eBay's DFS questions typically fall into three categories, reflecting real-world engineering scenarios. First, tree and binary tree traversals are common, such as finding paths, calculating sums, or validating structures, mirroring tasks in eBay's product hierarchy or category trees. Second, graph connectivity problems involve finding connected components, detecting cycles, or checking reachability, which relate to user networks or item associations. Third, backtracking and pathfinding challenges, like generating permutations or finding specific sequences, simulate search and filtering logic on eBay's platform. Expect problems to be framed around data structures like adjacency lists or tree nodes, with constraints emphasizing optimal recursion or iterative solutions.

How to Prepare — Study Tips with One Code Example

To prepare, focus on core concepts: understand recursive and iterative (stack-based) DFS implementations, memorize time/space complexity (O(V+E) for graphs), and practice backtracking patterns. Start with basic tree traversals before advancing to graph problems. Use a consistent template for DFS to reduce errors during interviews. Below is a key pattern for a recursive DFS to find if a path exists in a graph from a source to a target—a common eBay-style problem for checking connections, such as user interactions or item linkages.

def has_path_dfs(graph, src, target, visited=None):
    if visited is None:
        visited = set()
    if src == target:
        return True
    visited.add(src)
    for neighbor in graph.get(src, []):
        if neighbor not in visited:
            if has_path_dfs(graph, neighbor, target, visited):
                return True
    return False

Recommended Practice Order

Follow this sequence to build proficiency efficiently. Begin with basic tree DFS (e.g., inorder traversal, maximum depth). Move to graph DFS fundamentals (e.g., connected components, cycle detection). Then tackle backtracking applications (e.g., subsets, permutations). Finally, solve eBay-specific problems from platforms like CodeJeet to simulate interview conditions. Prioritize quality over quantity—analyze each solution's time and space complexity, and practice verbalizing your thought process. This order ensures you develop a solid foundation before handling complex scenarios.

Practice Depth-First Search at eBay