Min-Heap Pop (Sift Down)

Remove the minimum value, move the last item to the root, and sift downward.

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(log n)
Space: O(1) extra @end

sift down After removing the root, the last value moves to the root and swaps with the smaller child until order is restored.

R DSA Implementation

basic.R

list_string <- function(values) paste0("[", paste(values, collapse = ", "), "]")
heap_insert <- function(heap, value) {
  heap <- c(heap, value)
  child <- length(heap)
  while (child > 1) {
    parent <- floor(child / 2)
    if (heap[parent] <= heap[child]) break
    tmp <- heap[parent]; heap[parent] <- heap[child]; heap[child] <- tmp
    child <- parent
  }
  heap
}
heap_pop <- function(heap) {
  smallest <- heap[1]
  heap[1] <- heap[length(heap)]
  heap <- heap[-length(heap)]
  parent <- 1
  while (TRUE) {
    left <- parent * 2
    right <- left + 1
    if (left > length(heap)) break
    child <- left
    if (right <= length(heap) && heap[right] < heap[left]) child <- right
    if (heap[parent] <= heap[child]) break
    tmp <- heap[parent]; heap[parent] <- heap[child]; heap[child] <- tmp
    parent <- child
  }
  list(value = smallest, heap = heap)
}
heap <- c(1, 4, 2, 9, 6, 7)
result <- heap_pop(heap)
cat(result$value, " -> ", list_string(result$heap), "\n", sep = "")

@end @output 1 -> [2, 4, 7, 9, 6] @end