Maximum Score of Non-overlapping Intervals
A hard-tier problem at 31% community acceptance, tagged with Array, Binary Search, Dynamic Programming. Reported in interviews at Sprinklr and 0 others.
You've got intervals with scores, and you need to pick the non-overlapping ones that sum to the highest total. Sprinklr has asked this one. It's a HARD problem with a 31% acceptance rate, which means most candidates either miss the sorting trick, botch the DP state transition, or time out on the binary search logic. This is the kind of problem where the obvious greedy approach (sort by end time, pick greedily) fails because you're maximizing score, not count. You need DP plus binary search to find the latest non-overlapping interval before each candidate. If you hit this live and blank on the pattern, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Maximum Score of Non-overlapping Intervals"
Maximum Score of Non-overlapping Intervals 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 FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know.
Get StealthCoderThe trap is thinking greedy works here. It doesn't. You sort intervals by end time, then use DP where dp[i] is the maximum score using intervals up to i. For each interval, you either skip it or take it. If you take it, you add its score to the best solution before it non-overlaps. That's where binary search comes in: you search the sorted array for the rightmost interval that ends before the current one starts, then recurse into its DP value. Most candidates either implement the binary search wrong, use the wrong comparison logic, or forget to sort by end time first. The acceptance rate is low because the layered complexity (sorting plus DP plus binary search) trips people up in an interview setting. StealthCoder is the hedge if you haven't drilled interval overlaps with DP recently. The problem leans on Array, Binary Search, Dynamic Programming, and Sorting all at once.
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Maximum Score of Non-overlapping Intervals 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. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Maximum Score of Non-overlapping Intervals interview FAQ
Why doesn't greedy (always pick the highest-scoring interval) work here?+
Because one high-scoring interval might block you from picking many smaller overlapping ones that sum higher. You need DP to explore both choices: include the current interval or skip it. That exhaustive exploration is what greedy skips.
What's the binary search doing in this problem?+
After sorting by end time, for each interval you need to find the rightmost earlier interval that doesn't overlap with it. That search is O(log n), not O(n). Without it, your DP becomes O(n^2) and times out on large inputs.
Is this still asked at Sprinklr or other companies?+
Sprinklr has confirmed this problem. It's relatively rare (only one company in the reported data), which suggests it's a specialist ask. Check the company's interview guides for recent DP-heavy problems.
What's the most common mistake on this problem?+
Sorting by start time instead of end time, or forgetting to binary search altogether and doing a linear scan. Both break the complexity. The second mistake kills your runtime on large test cases.
How does this relate to the classic weighted job scheduling problem?+
It's almost the same pattern. Weighted job scheduling also uses sorting by end time, DP, and binary search to find the latest non-conflicting job. If you've solved that, this should feel familiar. If not, expect to learn the pattern here.
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