Jump Game II
A medium-tier problem at 42% community acceptance, tagged with Array, Dynamic Programming, Greedy. Reported in interviews at ConsultAdd and 30 others.
Jump Game II hits your screen and you freeze: you need to reach the last index with minimum jumps, and you can jump up to nums[i] steps from position i. About 41% of candidates solve it, which means half the people in your interview cohort are guessing or grinding through dynamic programming when there's a greedy pattern that solves it in one pass. Amazon, Expedia, Groupon, and 28 other companies ask this. If you blank on the trick mid-assessment, StealthCoder surfaces the optimal path in seconds, invisible to the proctor.
Companies that ask "Jump Game II"
Jump Game II is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE.
Get StealthCoderThe trap is dynamic programming: you can build a DP table to track min jumps to each position, but it's O(n squared) and slow. The greedy insight is cleaner: track the farthest index reachable with your current number of jumps, and when you can't go further, increment the jump count. You iterate once, updating the max range you can hit, and know exactly when you must jump again. Common fail: forgetting to check if you're already at the last index before incrementing jumps, or losing track of the boundary between current and next range. It's asked across Array, Dynamic Programming, and Greedy topics. Hit a wall on this during the live OA and StealthCoder gives you the working greedy loop without the DP overhead.
Pattern tags
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Jump Game II recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Jump Game II interview FAQ
Is Jump Game II still asked at big tech companies?+
Yes, frequently. Amazon, Expedia, Groupon, Zomato, and PhonePe all report asking it. It's a medium-difficulty classic that filters candidates who understand greedy vs. brute force. If you're prepping for any of those, this is a solid hedge.
Why does dynamic programming feel natural but fail here?+
DP works but it's O(n squared) because you check every reachable position for each step. Greedy avoids the inner loop by tracking the farthest you can reach with jumps so far. When you exhaust that range, you must jump again. It's the same problem solved in O(n) with a shift in perspective.
What's the core trick to the greedy approach?+
Maintain two pointers or boundaries: the farthest index reachable with current jumps, and the farthest you can reach if you jump now. Iterate through the array. When you hit the current boundary, increment jumps and update to the next boundary. One pass, done.
How does Jump Game II differ from the first Jump Game problem?+
First Jump Game asks 'can you reach the end' (yes/no), solvable with greedy in one pass. Jump Game II asks 'minimum jumps to reach the end' (a number). The second is harder because you must optimize, not just prove reachability. That's why it's Medium and why greedy shines.
What mistake do most people make in the live interview?+
Forgetting the jump count is incremented when you exhaust the current range, not when you exceed the array length. Also, edge case: if the array has one element, return 0 jumps immediately. Greedy logic breaks if you don't guard that first.
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