← Two Sigma Interview Insights
My first instinct was BFS and I started coding it up before realizing that's way heavier than needed.
Start by clarifying the problem and edge cases, then propose a greedy algorithm that tracks the furthest reachable index. Explain how you can determine reachability in a single pass, and optionally mention a dynamic programming alternative for comparison.
Pro tip: Emphasize the greedy approach's O(n) time and O(1) space efficiency, and discuss how you would handle edge cases like empty arrays or zero jumps. This shows you consider both optimality and robustness.
Confirm that the array contains non-negative integers, that you start at index 0, and that you need to determine if the last index is reachable. Ask about edge cases such as empty array or single element.
Explain that at any index i, you can jump to any index up to i + nums[i]. The goal is to see if you can extend your reach to or beyond the last index.
Iterate through the array while maintaining the maximum reachable index. If the current index exceeds the maximum reachable, return false; otherwise, update the maximum reachable with i + nums[i].
State that the greedy approach runs in O(n) time and O(1) space, making it optimal. Mention that a dynamic programming approach would be O(n^2) time and O(n) space, but is less efficient.
Walk through a simple example like [2,3,1,1,4] to show it returns true, and [3,2,1,0,4] to show it returns false. Discuss how the algorithm handles these cases.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.