, due to sorting.

🧺 Space complexity: O(1) (in-place sort).

Method 2 – Max Heap (Optimal for Large n, Small k)

Intuition

Maintain a max heap of size k. Iterate through the array, keeping only the k smallest elements seen so far.

Approach

Build a max heap with the first k elements.
For each remaining element, if it is smaller than the heap's maximum, replace the maximum and re-heapify.
At the end, the heap contains the k smallest elements.

Code

[{"language":"C++","code":"class Solution {\npublic:\n    vector<int> kSmallest(vector<int>& arr, int k) {\n        priority_queue<int> maxHeap;\n        for (int i = 0; i < arr.size(); ++i) {\n            if (maxHeap.size() < k) maxHeap.push(arr[i]);\n            else if (arr[i] < maxHeap.top()) {\n                maxHeap.pop();\n                maxHeap.push(arr[i]);\n            }\n        }\n        vector<int> ans;\n        while (!maxHeap.empty()) {\n            ans.push_back(maxHeap.top());\n            maxHeap.pop();\n        }\n        return ans;\n    }\n};","lang":"cpp","html":"<pre class=\"shiki shiki-themes github-light github-dark\" style=\"background-color:#fff;--shiki-dark-bg:#24292e;color:#24292e;--shiki-dark:#e1e4e8\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color:#D73A49;--shiki-dark:#F97583\">class</span><span style=\"color:#6F42C1;--shiki-dark:#B392F0\"> Solution</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\"> {</span></span>\n<span class=\"line\"><span style=\"color:#D73A49;--shiki-dark:#F97583\">public:</span></span>\n<span class=\"line\"><span style=\"color:#6F42C1;--shiki-dark:#B392F0\">    vector</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">&#x3C;</span><span style=\"color:#D73A49;--shiki-dark:#F97583\">int</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">> </span><span style=\"color:#6F42C1;--shiki-dark:#B392F0\">kSmallest</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">(</span><span style=\"color:#6F42C1;--shiki-dark:#B392F0\">vector</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">&#x3C;</span><span style=\"color:#D73A49;--shiki-dark:#F97583\">int</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">></span><span style=\"color:#D73A49;--shiki-dark:#F97583\">&#x26;</span><span style=\"color:#E36209;--shiki-dark:#FFAB70\"> arr</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">, </span><span style=\"color:#D73A49;--shiki-dark:#F97583\">int</span><span style=\"color:#E36209;--shiki-dark:#FFAB70\"> k</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">) {</span></span>\n<span class=\"line\"><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">        priority_queue</span><span style=\"color:#D73A49;--shiki-dark:#F97583\">&#x3C;int></span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\"> maxHeap;</span></span>\n<span class=\"line\"><span style=\"color:#D73A49;--shiki-dark:#F97583\">        for</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\"> (</span><span style=\"color:#D73A49;--shiki-dark:#F97583\">int</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\"> i </span><span style=\"color:#D73A49;--shiki-dark:#F97583\">=</span><span style=\"color:#005CC5;--shiki-dark:#79B8FF\"> 0</span><span style=\"color:#24292E;--shiki-dark:#E1E4E8\">; i </span>&#

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