Maximum Value
Reported by candidates from TikTok's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
TikTok's Maximum Value question (February 2024) is testing your ability to find an optimal subset or configuration under constraints. Candidates often blank on whether to use greedy, dynamic programming, or brute force because the problem statement is sparse. The real trick is identifying what "maximum" means in context: are you maximizing a sum, a product, a count, or something else. StealthCoder is your safety net if you freeze on the live assessment and need the solution pattern fed to you in real time.
Pattern and pitfall
Without the full problem text, the pattern likely hinges on either greedy selection (pick the best local option repeatedly) or dynamic programming (build up the optimal solution from subproblems). TikTok favors problems where the "obvious" greedy approach fails and you need to track state across decisions. The common pitfall is assuming a single pass works. You'll probably need to sort, then either iterate with memoization or build a DP table. If it's a constrained optimization problem, pay attention to edge cases: empty inputs, single elements, negative numbers, ties. StealthCoder handles the pattern recognition so you can focus on implementation details during the live OA.
If this hits your live OA and you blank, StealthCoder solves it in seconds, invisible to the proctor.
You can drill Maximum Value 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.
Get StealthCoderRelated leaked OAs
You've seen the question.
Make sure you actually pass TikTok's OA.
TikTok 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 Value FAQ
Is this a greedy or DP problem?+
If a single greedy pass gets you the right answer on examples, test with a case where local optima diverge from global. TikTok usually requires DP or backtracking for 'maximum' problems. Assume DP unless greedy is obviously correct.
What are the edge cases I should test?+
Empty array, single element, all negatives, all positives, ties, and zero. Also test constraint boundaries: if there's a size limit or value range, push both. TikTok's test suite usually includes one tricky edge case.
How do I prepare for this in 48 hours without the full problem?+
Master two patterns: subset sum with DP and greedy selection with sorting. Review LeetCode 198 (House Robber) and 55 (Jump Game). Both teach the constraint tracking that TikTok likes. Then memorize the DP template for 1D optimization.
Will the solution fit in time and space?+
If it's DP, O(n) or O(n^2) space is typical. Time is usually O(n log n) for sort plus O(n) or O(n^2) for the core logic. If you're over O(n^3), you're on the wrong path. Backtrack and re-read the constraints.
Should I code the brute force first or jump to optimized?+
Code brute force first on paper, test it on examples, then optimize. TikTok judges often accept brute force if it's correct and passes time limits. Don't over-engineer. If you hit time limit, add memoization or DP state.