Maximum Final
Reported by candidates from Amazon's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
Amazon's 'Maximum Final' hit the OA circuit in January 2024 and it's a deceptive greedy problem that trips up candidates who overthink it. You've got an array, and you're making moves to maximize some final value. The catch is figuring out which moves actually matter and which are noise. This is the kind of problem where the brute-force instinct will timeout, but the greedy insight is clean once you see it. StealthCoder can catch you if the greedy pattern doesn't click in the moment.
Pattern and pitfall
The core trick here is recognizing that you don't need to simulate every possible sequence of operations. Greedy problems at Amazon usually hinge on a local choice that guarantees a global optimum. With 'Maximum Final', the insight is typically that you're either picking elements to maximize, or you're performing operations that reduce the array in a way that preserves the maximum. Read the problem statement carefully for what 'final' means: is it the sum of remaining elements, the last element standing, or something else. The common pitfall is trying dynamic programming when greedy works. Test your greedy hypothesis against small examples before you code. If you blank on the pattern during the live OA, StealthCoder will identify it and show you the approach.
If this hits your live OA and you blank, StealthCoder solves it in seconds, invisible to the proctor.
You can drill Maximum Final cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Built by an Amazon engineer who would have shipped this the night before his JPMorgan OA if he'd had it.
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Amazon reuses patterns across OAs. Built by an Amazon engineer who would have shipped this the night before his JPMorgan OA if he'd had it. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Maximum Final FAQ
Is this a simulation problem or a math problem?+
It's greedy with a math intuition underneath. You're not simulating every step. Instead, you figure out the invariant: what property of the array doesn't change, or what's the optimal final state. Then work backward or use a single pass to achieve it.
Do I need to try all orderings of operations?+
No. That's the timeout trap. Greedy problems let you commit to a choice (pick the max, pick the min, process left to right, etc.) without backtracking. If your solution is exponential or even O(n^2), you're off the track.
What if the array is negative or zero?+
Edge case to test. If the final value can go negative, you might be choosing not to pick certain elements, or you might be forced to. Make sure your greedy logic handles zero and negative numbers without special-casing weirdly.
How much time should I spend on this during the OA?+
15-20 minutes to understand the problem and nail the greedy insight. Another 10 minutes to code and test. If you're still confused after 20 minutes, move on and come back. Don't lose the whole OA to one problem.
Is this problem still showing up at Amazon in late 2024?+
Amazon cycles through similar greedy and array patterns frequently. The exact problem might be remixed (different operation names, different final metric), but the underlying greedy intuition stays relevant. Expect variations.