Add binary heap (min-heap) implementation in R#296
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Pull request overview
Adds a new data_structures/binary_heap.r script implementing a vector-backed min binary heap in R, intended to support priority-queue style usage consistent with other simple data-structure scripts in this repository.
Changes:
- Introduces
push(heap, value),pop(heap), andpeek(heap)operations for a min-heap stored in a plain R vector. - Adds inline documentation describing heap properties, complexities, applications, and example usage.
siriak
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Jun 11, 2026
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Please address Copilot's comments
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| # A binary heap is a complete binary tree where each node is smaller than or | ||
| # equal to its children (min-heap). The minimum is always at the root. |
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| i <- 1 | ||
| child <- 0 | ||
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| # Test | ||
| if (sys.nframe() == 0){ | ||
| h <- c() | ||
| h <- push(h, 5) | ||
| h <- push(h, 3) | ||
| h <- push(h, 8) | ||
| h <- push(h, 1) | ||
| h <- push(h, 9) | ||
| h <- push(h, 2) | ||
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| print(peek(h)) | ||
| print(h) | ||
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| res <- pop(h) | ||
| print(res$value) | ||
| print(res$heap) | ||
| } |
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Description
Adds a binary heap (min-heap) implementation to the
data_structuresdirectory.The heap is represented as a plain R vector using value-passing semantics,
consistent with the existing simple data-structure implementations in the repo.
Operations
push(heap, value)— insert a value and sift up — O(log n)pop(heap)— extract the minimum and sift down — O(log n), returnslist(value, heap)peek(heap)— view the minimum without removing it — O(1)Checklist
.rfile extension