← Crowdstrike Interview Insights

Crowdstrike·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

Crowdstrike coding round, pretty standard grid traversal problem. Nothing too surprising but it's the kind of question where you either know BFS/DFS cold or you fumble around for 20 minutes.

Questions Asked (1)

Q1

Given a 2D binary grid where 1s represent land and 0s represent water, count the total number of islands, where an island is a group of 1s connected horizontally or vertically.

Algorithms & Data Structures
Author's notes

Classic problem, I knew it immediately.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Use a graph traversal algorithm like DFS or BFS to explore each unvisited land cell and mark all connected land cells as visited, incrementing the island count for each traversal. Alternatively, use Union-Find to group connected land cells and count distinct sets. Clearly state the time and space complexity.

Pro tip: Mention that you can optimize space by modifying the grid in-place (e.g., changing '1' to '0') to mark visited cells, but discuss the trade-off of mutating input. Also, be prepared to discuss handling edge cases like empty grid or all water.

1. Clarify and Confirm

Restate the problem to ensure understanding, ask about edge cases (empty grid, all water, all land) and constraints (grid size, recursion depth).

2. Choose Approach

Decide between DFS, BFS, or Union-Find based on constraints and preferences. Explain why you chose it.

3. Outline Algorithm

Describe the steps: iterate through each cell; when a '1' is found, increment count and traverse all connected '1's, marking them visited.

4. Analyze Complexity

State time complexity O(rows*cols) and space complexity O(rows*cols) for visited set or recursion stack, or O(1) if modifying in-place.

5. Discuss Optimizations and Trade-offs

Mention potential optimizations like early termination, using iterative BFS to avoid recursion limits, or Union-Find for dynamic scenarios.

Key Points to Mention

  • Graph traversal techniques: DFS (recursive/iterative) and BFS
  • Union-Find (Disjoint Set Union) as an alternative approach
  • Time and space complexity analysis
  • Handling edge cases: empty grid, single row/column, all water/land
  • In-place modification vs. using a separate visited matrix
  • Recursion depth concerns and iterative alternatives

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