Construct String With Repeat Limit
A medium-tier problem at 71% community acceptance, tagged with Hash Table, String, Greedy. Reported in interviews at Arista Networks and 1 others.
Construct String With Repeat Limit is a medium-difficulty string problem that sits at roughly 71% acceptance, yet it trips up candidates who reach for the obvious greedy move without a fallback. You've got a character count, a repeat limit, and you need to build the lexicographically largest string without violating the constraint. Arista Networks and Fortinet have both asked this. The trick isn't just greedily placing your highest character. When you hit the repeat limit, you need to know what to place next, and that decision separates a quick solve from a false start during the live OA. If this problem hits your assessment and you blank on the order of operations, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Construct String With Repeat Limit"
Construct String With Repeat Limit 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 Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE.
Get StealthCoderThe core pattern is greedy with a safety valve. You want to place the largest available character as many times as the repeat limit allows, then immediately place the next-largest character once, then back to the largest. The catch: if you've run out of smaller characters to act as the 'blocker,' you're stuck. This is where a max-heap or sorted approach shines. You track character frequencies, extract greedily, and when you hit the repeat limit, you peek at what's next in line. If nothing's there, your string ends. Most candidates start with a simple sorted loop and hit this edge case during testing. Hash tables track counts, greedy determines placement order, and heap or sorting handles the 'what's next' question efficiently. Common pitfall: assuming you can always find a blocker character, or iterating through characters inefficiently. StealthCoder hedges the moment you realize the greedy path has a flaw mid-assessment.
Pattern tags
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Make sure you actually pass it.
Construct String With Repeat Limit 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. Made by a working Amazon engineer who got tired of watching qualified friends bomb OAs they'd solve cold in an IDE. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Construct String With Repeat Limit interview FAQ
Is this really just 'always pick the biggest character'?+
No. You pick the biggest character up to the repeat limit, then must place something smaller to reset the count. The trick is handling the case where no smaller character exists. That's when your string terminates early. Greedy works, but it's greedy with a pause, not greedy all the way.
Do I need a heap or can I sort once and loop?+
Sorting once and looping works if you manage state carefully. A max-heap is cleaner because you extract the largest, use it, and re-insert if it has remaining count. Either way, the complexity is similar. Pick whatever feels natural under time pressure.
How often does Arista or Fortinet actually ask this?+
Both companies have reported asking it. It's not the most frequent medium problem at either firm, but it's on the board. At 71% acceptance, it's easier than many mediums, so missing it during a live OA would be a regrettable miss.
What's the main edge case I'll hit?+
Running out of blocker characters. You've placed the largest character k times, you need to place a smaller one, but none remain with count > 0. Your loop must exit gracefully and return what you've built so far, not crash or loop infinitely.
How does Hash Table and Heap relate here?+
Hash Table (or counting array) tracks character frequencies. Heap organizes characters by value so you always access the max efficiently. Together they let you place greedily without scanning the entire alphabet every iteration, keeping time complexity reasonable.
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