Anthropic·Software Engineer·Technical Phone Screen·Senior

Senior

May 2026

Summary

Anthropic software engineer interview with a graph traversal problem that looks straightforward until you actually read the domain-filtering requirements carefully. The BFS skeleton is easy enough but the root domain extraction tripped me up a bit.

Questions Asked (1)

Given a directed graph representing a web link structure and a seed URL, return all pages reachable from the seed that share the seed's root domain, discovered via BFS, with duplicates removed and results in visitation order.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

The BFS part was fine, I've done enough of those.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints and edge cases, then outline a BFS traversal that tracks visited nodes and filters by root domain. Emphasize efficiency, correctness, and how you would handle large graphs or distributed crawling.

Pro tip: Mention that you would normalize URLs (e.g., handle redirects, trailing slashes, case sensitivity) before domain comparison to avoid missing or duplicating pages. Also, discuss the trade-off between in-memory visited sets and external storage for scalability.

1. Clarify Requirements and Edge Cases

Ask about graph size, memory limits, URL normalization rules, and whether the seed's root domain includes subdomains. Confirm output format and handling of cycles.

2. Design BFS Traversal

Use a queue for BFS, a set for visited URLs, and a list for results. Start with the seed, enqueue its neighbors, and process level by level.

3. Implement Domain Filtering

Extract the root domain from each URL and compare with the seed's root domain. Only enqueue and add to results if they match.

4. Handle Duplicates and Order

Use a visited set to avoid revisiting nodes. Append to results when first visited to maintain BFS visitation order.

5. Analyze Complexity and Optimizations

Discuss time and space complexity (O(V+E) time, O(V) space). Suggest optimizations like parallel BFS or distributed crawling for large-scale graphs.

Key Points to Mention

BFS guarantees shortest path and visitation order
Visited set prevents cycles and duplicates
Root domain extraction and comparison (e.g., using tldextract or regex)
URL normalization to handle redirects, case, and trailing slashes
Time and space complexity analysis
Scalability considerations for large graphs (e.g., distributed BFS, external storage)

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.