Monotone Increasing Digits
A medium-tier problem at 49% community acceptance, tagged with Math, Greedy. Reported in interviews at SAP and 1 others.
Monotone Increasing Digits is a medium-difficulty problem that tests whether you understand how to construct valid numbers under constraints, not just validate them. You're given an integer and need to find the largest number less than or equal to it where each digit is greater than or equal to the previous one. It sounds simple until you hit the first test case and realize the greedy approach fails. SAP and Credit Karma both ask this one. The acceptance rate sits below 49 percent, which means most candidates either brute-force incorrectly or miss the greedy insight entirely. If this lands in your assessment and you blank on the pattern, StealthCoder surfaces a working solution invisibly while you stay focused on execution.
Companies that ask "Monotone Increasing Digits"
Monotone Increasing Digits 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 trap is thinking left-to-right greedy works. It doesn't. When you find a digit that breaks the monotone property, you can't just fix it locally. You have to backtrack, decrement an earlier digit, and fill everything after it with nines to maximize the result. The real trick is recognizing that you're searching backwards for the first position where decreasing the digit still keeps the number monotone, then setting all digits after that to nine. Most candidates get stuck because they try to patch violations as they go rather than undoing them strategically. The Math and Greedy labels are accurate: you're doing arithmetic manipulation, and the greedy choice is to make each digit as large as possible while maintaining the constraint. If you haven't drilled this exact pattern before, StealthCoder solves it in seconds during a live assessment, showing you the backtracking logic without the proctor seeing a thing.
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Monotone Increasing Digits 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.
Monotone Increasing Digits interview FAQ
Why doesn't left-to-right greedy work here?+
Greedy fails because fixing a violation at position i by reducing digit i might force you to reduce earlier digits too, costing you a much larger result. You have to find the rightmost position where decreasing the digit keeps the monotone property intact, then maximize everything after it with nines. That's backward greedy, not forward.
Is this still asked at major companies?+
Yes. SAP and Credit Karma both report asking it. At below 49 percent acceptance, it's not a rote problem. It's testing whether you can think through a greedy insight that isn't obvious on first read, which is exactly what tech companies want to see.
What's the core algorithm I need to remember?+
Convert to a digit array, scan left to right to find the first violation, then scan backwards from that violation to find where decreasing a digit still satisfies the monotone constraint, decrement it, and set everything after to nine. The backward scan is the insight most people miss.
How does the Math topic connect to this problem?+
You're doing digit manipulation and arithmetic reasoning, not calculus or number theory. The Math label just means you're thinking about the structure of numbers and how to construct them, not applying a formula.
What's the time complexity I should aim for?+
O(n) where n is the number of digits, since you scan the array twice at most. Space is O(n) for the digit array. There's no way around linear time and space because you have to examine and possibly rewrite each digit.
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