Top-K with a Heap - JavaScript DSA

Keep only the largest k values by maintaining a small min-heap.

Algorithm

@steps

Store the heap in an array.
Compare parent and child indexes instead of building explicit tree nodes.
Swap only when the heap order is violated.
Print the deterministic final heap state for replay comparison. @end @complexity

Time: O(n log k)
Space: O(k) @end

bounded heap For top-k largest values, a min-heap of size k keeps the current cutoff at the root.

JavaScript DSA Implementation

basic.js

function listString(values) { return `[${values.join(", ")}]`; }
function heapInsert(heap, value) {
  heap.push(value);
  let child = heap.length - 1;
  while (child > 0) {
    const parent = Math.floor((child - 1) / 2);
    if (heap[parent] <= heap[child]) break;
    [heap[parent], heap[child]] = [heap[child], heap[parent]];
    child = parent;
  }
}
function heapPop(heap) {
  const smallest = heap[0];
  heap[0] = heap.pop();
  let parent = 0;
  while (true) {
    const left = parent * 2 + 1;
    const right = left + 1;
    if (left >= heap.length) break;
    let child = left;
    if (right < heap.length && heap[right] < heap[left]) child = right;
    if (heap[parent] <= heap[child]) break;
    [heap[parent], heap[child]] = [heap[child], heap[parent]];
    parent = child;
  }
  return smallest;
}
const values = [5, 1, 9, 3, 7, 2];
const heap = [];
for (const value of values) { heapInsert(heap, value); if (heap.length > 3) heapPop(heap); }
console.log(listString([...heap].sort((a, b) => b - a)));

@end @output [9, 7, 5] @end