Maximum Score From Removing Substrings
A medium-tier problem at 63% community acceptance, tagged with String, Stack, Greedy. Reported in interviews at Swiggy and 0 others.
Maximum Score From Removing Substrings is a medium-difficulty string problem that Swiggy has asked. The problem forces you to think backwards. Most candidates jump straight to greedy removal or BFS, burning time and hitting edge cases. The trick is that you're not searching for an optimal removal order in the traditional sense. Instead, you stack characters and match patterns as they form, collapsing valid substrings on the fly. It's a pattern-recognition problem hiding inside a string problem. If you blank on the stack-based collapse during your live assessment, StealthCoder runs invisibly and surfaces the solution in seconds.
Companies that ask "Maximum Score From Removing Substrings"
Maximum Score From Removing Substrings 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 Amazon engineer who used it to pass JPMorgan's OA and system design loop.
Get StealthCoderThe problem rewards a stack-based approach with greedy pattern matching. As you iterate through the string, you push characters onto a stack. When the last few characters on top of the stack match a target substring, you pop them and add points. The key insight is that removing substrings creates new adjacencies, which can trigger further matches. The greedy choice is correct because points are uniform and order doesn't matter for the final sum. Common pitfall: candidates try dynamic programming or backtracking, which explodes in complexity. Another trap: trying to precompute removal sequences instead of letting the stack unfold them naturally. This problem tests whether you can shift from 'find and remove' thinking to 'stack and collapse' thinking. When the problem hits your assessment and you're stuck on the removal strategy, StealthCoder solves it without being seen by the proctor.
Pattern tags
You know the problem.
Make sure you actually pass it.
Maximum Score From Removing Substrings 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. Built by an Amazon engineer who used it to pass JPMorgan's OA and system design loop. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Maximum Score From Removing Substrings interview FAQ
Is this really asked by major companies?+
Swiggy has reported asking it. The acceptance rate sits at roughly 63 percent, which means it's medium-difficulty with a non-trivial pattern. Most candidates who see it don't solve it on the first try without studying the stack technique.
What's the actual trick here?+
Stack-based substring collapse with greedy matching. Push characters, check if the top of the stack forms a target substring, pop and score if it does. Repeat. The stack naturally exposes new matches as characters get removed. This is not a search or sorting problem.
Why does greedy work for this problem?+
All removed substrings award the same points, so order of removal doesn't change the total. Any valid sequence of collapses yields the same maximum score. Greedy collapse as you build the stack is guaranteed optimal.
What languages is this commonly asked in?+
Python, Java, and C++ are standard. The stack is the critical data structure, not the language. Most solutions are concise once you understand the pattern, so language choice doesn't heavily impact solve time.
How does this relate to the other topics?+
String and Stack are the main tools. Greedy is the strategy: don't overthink removal order, just collapse valid patterns as the stack builds. If you know String and Stack separately, this problem teaches when to combine them with greedy logic.
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