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Given a list of request timestamps (seconds) and a window size w, return the largest number of requests that land inside any window of length w.
import java.util.*;
class Solution {
// Sliding window over sorted timestamps — O(n log n).
static int peakWindow(int[] times, int w) {
Arrays.sort(times);
int best = 0, left = 0;
for (int right = 0; right < times.length; right++) {
while (times[right] - times[left] >= w) left++;
best = Math.max(best, right - left + 1);
}
return best;
}
}Every hiring process is a bet on a proxy — a school, a logo, a confident answer in a room. KodeQualify replaces the proxy with the artefact: the code they wrote, the cases it passed, the ones it didn't.
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Where someone studied doesn't compile. Rank on what the code did, then read the CV for context — not the other way round.
Problems in a real editor against real runtimes, with the standard library available. If the job is Go, the test is Go.
Same questions, same weights, same clock, same sandbox. Scores compare because the conditions are identical by construction.
Timed honestly, scored transparently, proctored — so the people who did the work aren't out-competed by the people who didn't.
Write the problem and its test cases. Before it can be published, KodeQualify executes your reference solution in an isolated sandbox — a question that fails its own tests never reaches a candidate.
Bundle published questions into a timed assessment with per-question points. Every invitation carries the same set, the same weights and the same clock — no improvising per candidate.
Every submission runs case by case and scores itself. Watch the funnel fill, then rank on the numbers underneath — with the failing diff there when someone asks you to justify the call.
// POST /api/code-test-questions → 202 Accepted
await createQuestion({
title: "Peak request window",
language: "go",
codeSnippet: referenceSolution,
testCases: [
{ input: "[1,2,3] 60", expectedOutput: "3",
isSample: true, weight: 1 },
{ input: "[] 60", expectedOutput: "0", weight: 2 },
],
});
// pending_validation → validating → publishedAuthor the problem, the reference solution and the weighted cases together. KodeQualify runs them in a sandbox and only publishes when the solution passes its own tests — so a broken question can never cost a candidate the role.
{
"candidate": "marco@example.com",
"assessment": "Backend Engineer · Screen",
"totalScore": 8,
"maxScore": 10,
"results": [
{ "case": "hidden #2", "passed": false, "weight": 2,
"expected": "0", "received": "1" }
],
"elapsedMinutes": 37,
"plagiarismSignal": null
}Partial credit is the point. Each case carries its own weight, so a candidate who solves the problem but misses one edge case reads as 8/10 — with the failing diff attached — instead of a shrug and a maybe.
# identical conditions, every candidate, every attempt
runtime go1.23 # pinned, not "whatever's installed"
cpu 2 vCPU
memory 2048 MB
network deny # no egress, no lookups
timeout 5000 ms
filesystem fresh microVM, destroyed on exit
# a faster laptop earns no points hereEvery submission runs in a single-use microVM with a pinned runtime, fixed CPU and memory, no network and a hard timeout. Nobody is scored on their laptop, their connection or the hour of day they sat the test.
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Candidates tell us it's the first screen that felt like the actual job — same editor, same runtime, real problems. And they get a score back instead of silence, which is the part they thank us for.

Engineering Manager, Plugable
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