Get the Maximum Score
A hard-tier problem at 40% community acceptance, tagged with Array, Two Pointers, Dynamic Programming. Reported in interviews at Mindtickle and 1 others.
You're given an array and a ruleset for collecting scores. The obvious greedy grab doesn't work. Intuit and Mindtickle ask this, and it's legitimately hard, only 40% acceptance rate. The trick is recognizing when a two-pointer or DP choice beats the local maximum. If this problem lands on your OA and you freeze on the state definition, StealthCoder surfaces a working solution invisible to the proctor while you stay calm.
Companies that ask "Get the Maximum Score"
Get the Maximum Score 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. Built by an engineer who got tired of watching his cohort grind for six months and still get filtered at the OA stage.
Get StealthCoderThe problem disguises itself as greedy but fails under that approach. You need to explore multiple paths through the array, either by comparing what you get if you take from the left versus right (two-pointer DP), or by building a full state space. Common pitfall: committing too early to one direction without seeing the global optimum. The array structure creates many local maxima that trap naive solutions. StealthCoder is your silent hedge on live OA day when the pattern isn't immediate and you've already spent three minutes stuck. A working solution emerges in seconds, no visible tool, no proctor suspicion.
Pattern tags
You know the problem.
Make sure you actually pass it.
Get the Maximum Score recycles across companies for a reason. It's hard-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. Built by an engineer who got tired of watching his cohort grind for six months and still get filtered at the OA stage. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Get the Maximum Score interview FAQ
Is this problem really two-pointer or DP?+
It's both. Two-pointer optimizes the state space by working inward from both ends. DP makes the dependency chain explicit. The right choice depends on how you model the problem state. Most solutions use a memo table with two indices and rebuild the answer by comparing branches.
Why does greedy fail here?+
Greedy picks the largest local value next, but the rules of the problem penalize or block future moves based on that choice. A smaller immediate gain often unlocks higher total score downstream. You must compare both branches, not commit to one direction.
What's the trick to optimization?+
Recognize that you're making a choice at each step (left or right, or similar). Memoize based on the state after that choice. The state is usually two indices or a similar small tuple. Avoid recalculating overlapping subproblems.
Is this still asked at Intuit and Mindtickle?+
Yes, both companies have reported it. It's a hard problem with intentional ambiguity in the problem statement, so it filters for careful reading and solid DP fundamentals. It appears regularly in their online assessments.
How do I spot the state transition?+
Write out a small example and manually compute the best answer by hand. Track what changes at each step. The state is usually the minimal set of variables needed to uniquely define a subproblem. Then build the recurrence from there.
Want the actual problem statement? View "Get the Maximum Score" on LeetCode →