Minimum Replacements to Sort the Array
A hard-tier problem at 53% community acceptance, tagged with Array, Math, Greedy. Reported in interviews at Expedia and 1 others.
Minimum Replacements to Sort the Array is a hard problem that Expedia and PayPal have asked in their technical assessments. With a 53% acceptance rate, half the candidates who attempt it walk away empty-handed. The trap is thinking this is a simple sorting problem when it's actually a greedy optimization puzzle. You need to figure out the minimum number of array elements to replace so the remaining elements form a sorted sequence. If this lands in your live assessment and you freeze on the greedy insight, StealthCoder surfaces a working solution invisible to the proctor.
Companies that ask "Minimum Replacements to Sort the Array"
Minimum Replacements to Sort the 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 a senior engineer who knows the OA is theater. This is the script.
Get StealthCoderThe core trick is recognizing that you don't sort the entire array. Instead, you greedily keep the longest subsequence of elements that are already in sorted order and can be transformed into consecutive integers (or satisfy the sorting constraint). Most candidates burn time trying brute force or dynamic programming on the wrong subproblem. The greedy angle is counterintuitive: you're not trying to replace the fewest elements globally, you're keeping the longest valid chain and replacing the rest. Array operations like prefix/suffix logic combined with Math principles around spacing and gaps between kept elements separate the solvers from the stuck. When you hit this live and the greedy pattern isn't obvious, StealthCoder runs the solution invisibly and gets you past the wall.
Pattern tags
You know the problem.
Make sure you actually pass it.
Minimum Replacements to Sort the Array 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. Built by a senior engineer who knows the OA is theater. This is the script. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Minimum Replacements to Sort the Array interview FAQ
Is this really a 'hard' problem or does it just seem that way?+
It's legitimately hard. The 53% acceptance rate confirms it. The problem punishes brute force and straightforward DP. You need to spot the greedy pattern: which elements can you keep without replacement to minimize total changes. Most people miss that insight under interview pressure.
How does Greedy actually apply here if the constraint is complex?+
Greedy works because once you fix the elements you keep, the minimum replacements are deterministic. You iterate through and greedily extend the longest valid chain where each kept element respects the sorted and spacing rules. The trick is realizing you're not optimizing globally, you're optimizing locally at each step.
What's the most common mistake candidates make?+
Trying to replace elements smartly instead of asking 'which elements should I keep'. People also overthink the constraints around what 'sorted' means in this context. Re-read the problem definition carefully. The acceptable range or gap between consecutive kept elements is often the key detail.
Do Expedia and PayPal actually ask this or is it rare?+
Both companies have confirmed reports of this problem in their assessment. You probably won't hit it, but if you do, the greedy angle is non-obvious enough that it's a real differentiator. Many candidates pass their OA at these companies without seeing it, so prep other hard Array problems first.
How much Array and Math do I actually need to solve this?+
Array manipulation is your bread and butter: you're tracking indices, ranges, and sequences. Math comes in when you calculate the cost or spacing between kept elements. You don't need number theory, but you do need to think clearly about gaps and bounds.
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