Visa·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Visa coding round, one algorithm question the whole time. Pretty standard greedy problem but the pressure of explaining your reasoning out loud while coding makes it feel harder than it looks on paper.

Questions Asked (1)

Given an integer array where each element represents the maximum jump length from that position, determine whether you can reach the last index starting from index 0.

Algorithms & Data Structures

Author's notes

I knew this one, which was a relief.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then propose a greedy solution that tracks the farthest reachable index while scanning the array. Explain why the greedy approach is optimal and analyze its time and space complexity.

Pro tip: After presenting the greedy solution, mention that a dynamic programming approach exists but is less efficient, showing you understand trade-offs. Also, proactively discuss edge cases like empty arrays or single-element arrays to demonstrate thoroughness.

1. Clarify and Confirm

Restate the problem in your own words and ask clarifying questions about input constraints, edge cases, and expected output format.

2. Brainstorm Approaches

Discuss possible strategies such as dynamic programming or greedy, and compare their time and space complexities to justify your choice.

3. Design the Algorithm

Outline the greedy algorithm: iterate through the array, maintain the farthest reachable index, and update it based on the current index and jump length.

4. Walk Through an Example

Trace the algorithm on a sample input to demonstrate correctness and help the interviewer follow your logic.

5. Analyze Complexity and Edge Cases

State the time and space complexity, and discuss how the algorithm handles edge cases like empty arrays, single element, or unreachable last index.

Key Points to Mention

Greedy approach: track the farthest reachable index in a single pass.
Time complexity: O(n) and space complexity: O(1).
Edge cases: empty array, single element, zero jumps, unreachable last index.
Comparison with dynamic programming: O(n^2) time and O(n) space, but greedy is optimal.
Proof of correctness: if the farthest reachable index is less than the current index, return false.
Handling of large inputs and potential integer overflow (if applicable).

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