Determine the Minimum Sum of a k-avoiding Array
A medium-tier problem at 60% community acceptance, tagged with Math, Greedy. Reported in interviews at Infosys and 0 others.
You've got a medium-difficulty greedy problem that Infosys reportedly asks, and the acceptance rate sits right around 60 percent. That middle band is the trap zone: it looks doable until you start coding, then the greedy choice becomes ambiguous. The problem asks you to build an array under a constraint (k-avoiding), minimizing the sum. The trick isn't the math. It's knowing which elements to pick first and why the obvious greedy path fails. If this lands in your Infosys OA and you're unsure of the pattern, StealthCoder surfaces a working solution invisible to the proctor in seconds.
Companies that ask "Determine the Minimum Sum of a k-avoiding Array"
Determine the Minimum Sum of a k-avoiding Array 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 core challenge is figuring out what 'k-avoiding' means operationally, then proving your greedy choice is optimal. Most candidates start by trying to minimize each element individually, which sounds right but breaks the constraint. The real play is recognizing that you can't pick arbitrary elements; the k-avoiding property ties one element's validity to the presence or absence of others. This is where Math and Greedy intersect: you need to understand the mathematical relationship, then decide the order in which to commit to elements. The trap is thinking you can build the array left-to-right like normal. You often can't. Once you see the structure, the greedy priority becomes obvious, but until then, you're guessing. StealthCoder hedges that moment where you'd otherwise waste ten minutes on a dead approach.
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Determine the Minimum Sum of a k-avoiding Array 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 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.
Determine the Minimum Sum of a k-avoiding Array interview FAQ
Is this problem actually hard or does it just look hard?+
Acceptance rate of 60 percent tells you it's hard enough that most people miss the pattern but not hard enough that it's truly rare. The difficulty is recognizing the constraint structure and the correct greedy order, not the implementation. Once you name the insight, it's straightforward code.
Do I need heavy number theory or is it mostly logical reasoning?+
It's listed under Math and Greedy. You'll need solid arithmetic and modulo logic to understand the k-avoiding property, then greedy reasoning to decide which elements to prioritize. No advanced number theory, but you can't skip the Math part.
Will the obvious greedy approach work, or is there a trap?+
The obvious approach almost always fails. Your first instinct will be to pick the smallest available numbers, but k-avoiding means some numbers are blocked based on what you've already chosen. You have to find the non-obvious greedy criterion that respects the constraint.
How does this relate to other Infosys interview problems?+
Infosys asks greedy and constraint-satisfaction problems often. This one combines both. If you've solved interval scheduling or task ordering problems, the structure is similar: prove your greedy choice is safe, then execute it in the right order.
Can I brute force this or do I need to be clever?+
Brute force will time out unless the array is tiny. The problem is designed to force you to find the greedy insight. That's the whole point of Medium difficulty. Brute force is the safety-net fallback, not the solution.
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