tests and docs

explanations/Min_Binary_Heap.md

@@ -0,0 +1,87 @@
+# Explanations by AI using my code as example
+
+## Min Binary Heap
+
+> Source: `trees/heap/minHeap.go`
+
+A binary heap is a complete binary tree flattened into a single slice
+(`MinHeap.Array`). No node pointers — the tree shape lives in the index math.
+
+### The invariant
+
+Every parent is **≤** both its children. The smallest value therefore always sits
+at the root (`Array[0]`). This is a *partial* order: siblings are unordered, so the
+array is "loosely sorted", which is cheaper to maintain than a fully sorted array.
+
+### Index math (implicit tree)
+
+For a node at index `i`:
+
+| Relation     | Index       |
+| ------------ | ----------- |
+| left child   | `2*i + 1`   |
+| right child  | `2*i + 2`   |
+| parent       | `(i-1) / 2` |
+
+### The two repair operations
+
+Both walk one root-to-leaf path, so both are **O(log n)**.
+
+- **`siftUp(i)`** — used by `Insert`. A value that may be *too small* for its position
+  bubbles **up**, swapping with its parent while it's smaller than the parent.
+- **`siftDown(i)`** — used by `PopMin` and `Heapify`. A value that may be *too large*
+  sinks **down**, repeatedly swapping with its **smallest** child until both children
+  are ≥ it (or it hits a leaf).
+
+### Methods
+
+| Method       | What it does                                                    | Cost         |
+| ------------ | -------------------------------------------------------------- | ------------ |
+| `NewMinHeap` | returns an empty heap                                           | O(1)         |
+| `Insert`     | appends to the end, then `siftUp` to restore the invariant     | O(log n)     |
+| `PopMin`     | returns the root; see the swap-and-sink dance below            | O(log n)     |
+| `Heapify`    | bulk-builds a heap from an arbitrary slice (empty heap only)   | O(n)         |
+
+### PopMin, step by step
+
+You can't just delete `Array[0]` — that leaves a hole. Instead:
+
+1. Save the root (`Array[0]`) as the return value.
+2. Move the **last** element into the root slot.
+3. Zero the old last slot and shrink the slice by one (order matters — clear the slot
+   *before* reslicing, or the index is out of range).
+4. `siftDown(0)` to push that moved-up value back to its rightful depth.
+
+Returns `(zero, false)` when the heap is empty.
+
+> The zeroing (`Array[last] = zero`) only matters when `T` holds a pointer
+> (e.g. `string`, which `cmp.Ordered` allows) — it lets the GC reclaim the dropped
+> element instead of keeping it alive in the backing array.
+
+### Heapify: why it's O(n), not O(n log n)
+
+Inserting `n` items one by one would be O(n log n). `Heapify` is faster: it copies the
+slice, then calls `siftDown` on every **non-leaf** node, from the last parent up to the
+root:
+
+```go
+for i := len(h.Array)/2 - 1; i >= 0; i-- {
+    h.siftDown(i)
+}
+```
+
+Starting at `len/2 - 1` skips the leaves (they're already trivially valid heaps of
+size 1). Working bottom-up means each `siftDown` sinks into subtrees that are *already*
+valid heaps. Most nodes are near the bottom and barely move, so the total work sums to
+O(n), not O(n log n).
+
+It refuses to run on a non-empty heap (returns an error) to avoid clobbering existing
+data.
+
+### Summary
+
+- **Array + index math** = a tree with no pointers and cache-friendly memory.
+- **Invariant (parent ≤ children)** = the min is always `Array[0]`, peek is O(1).
+- **`siftUp` / `siftDown`** = the O(log n) repairs that keep the invariant after an
+  insert or a pop.
+- **`Heapify`** = build the whole heap in O(n) by sinking non-leaves bottom-up.

tests/treeTests/priorityQueue_test.go

@@ -0,0 +1,136 @@
+package tests
+
+import (
+	"math/rand"
+	"slices"
+	"testing"
+
+	"datastructures/trees/heap"
+)
+
+func TestPQPopEmpty(t *testing.T) {
+	q := heap.NewPriorityQueue[int]()
+	if v, ok := q.Pop(); ok {
+		t.Fatalf("Pop on empty queue = (%d, true), want (0, false)", v)
+	}
+}
+
+func TestPQPeekEmpty(t *testing.T) {
+	q := heap.NewPriorityQueue[int]()
+	if v, ok := q.Peek(); ok {
+		t.Fatalf("Peek on empty queue = (%d, true), want (0, false)", v)
+	}
+}
+
+func TestPQSizeTracksPushPop(t *testing.T) {
+	q := heap.NewPriorityQueue[int]()
+	if q.Size() != 0 {
+		t.Fatalf("new queue Size = %d, want 0", q.Size())
+	}
+	for i, v := range []int{9, 4, 7, 1} {
+		q.Push(v)
+		if q.Size() != i+1 {
+			t.Fatalf("after %d pushes Size = %d, want %d", i+1, q.Size(), i+1)
+		}
+	}
+	for want := 3; want >= 0; want-- {
+		q.Pop()
+		if q.Size() != want {
+			t.Fatalf("Size = %d, want %d", q.Size(), want)
+		}
+	}
+}
+
+func TestPQPeekReturnsMinWithoutRemoving(t *testing.T) {
+	q := heap.NewPriorityQueue[int]()
+	for _, v := range []int{8, 3, 5, 1, 9} {
+		q.Push(v)
+	}
+	v, ok := q.Peek()
+	if !ok || v != 1 {
+		t.Fatalf("Peek = (%d, %v), want (1, true)", v, ok)
+	}
+	// Peek must not mutate the queue.
+	if q.Size() != 5 {
+		t.Fatalf("Size after Peek = %d, want 5", q.Size())
+	}
+	v2, _ := q.Peek()
+	if v2 != v {
+		t.Fatalf("second Peek = %d, want same %d", v2, v)
+	}
+}
+
+func TestPQPopsInPriorityOrder(t *testing.T) {
+	in := []int{5, 3, 8, 1, 9, 2, 7, 0, 4, 6}
+	q := heap.NewPriorityQueue[int]()
+	for _, v := range in {
+		q.Push(v)
+	}
+
+	got := []int{}
+	for q.Size() > 0 {
+		// Peek must always agree with the next Pop.
+		p, ok := q.Peek()
+		if !ok {
+			t.Fatal("Peek returned ok=false while Size > 0")
+		}
+		v, ok := q.Pop()
+		if !ok {
+			t.Fatal("Pop returned ok=false while Size > 0")
+		}
+		if p != v {
+			t.Fatalf("Peek returned %d but Pop returned %d", p, v)
+		}
+		got = append(got, v)
+	}
+
+	want := slices.Clone(in)
+	slices.Sort(want)
+	if !slices.Equal(got, want) {
+		t.Fatalf("pop order = %v, want ascending %v", got, want)
+	}
+}
+
+func TestPQStrings(t *testing.T) {
+	q := heap.NewPriorityQueue[string]()
+	for _, s := range []string{"pear", "apple", "cherry", "banana"} {
+		q.Push(s)
+	}
+	got := []string{}
+	for q.Size() > 0 {
+		v, _ := q.Pop()
+		got = append(got, v)
+	}
+	want := []string{"apple", "banana", "cherry", "pear"}
+	if !slices.Equal(got, want) {
+		t.Fatalf("pop order = %v, want %v", got, want)
+	}
+}
+
+func TestPQFuzzAgainstSort(t *testing.T) {
+	rng := rand.New(rand.NewSource(7))
+	for trial := 0; trial < 200; trial++ {
+		n := rng.Intn(50)
+		in := make([]int, n)
+		for i := range in {
+			in[i] = rng.Intn(100)
+		}
+
+		q := heap.NewPriorityQueue[int]()
+		for _, v := range in {
+			q.Push(v)
+		}
+
+		got := []int{}
+		for q.Size() > 0 {
+			v, _ := q.Pop()
+			got = append(got, v)
+		}
+
+		want := slices.Clone(in)
+		slices.Sort(want)
+		if !slices.Equal(got, want) {
+			t.Fatalf("trial %d: got %v, want %v (input %v)", trial, got, want, in)
+		}
+	}
+}

trees/heap/heapAlgorithms.go

@@ -28,3 +28,43 @@ func HeapSrort[T cmp.Ordered](arg []T) []T {
 
 	return sorted
 }
+
+// PriorityQueue
+type PriorityQueue[T cmp.Ordered] struct {
+	heap MinHeap[T]
+}
+
+// NewPriorityQueue() -> creates a Priority Queue using min Heap
+func NewPriorityQueue[T cmp.Ordered]() *PriorityQueue[T] {
+	return &PriorityQueue[T]{}
+}
+
+// Push() -> adds new value to queue
+func (q *PriorityQueue[T]) Push(v T) {
+	q.heap.Insert(v)
+}
+
+// Pop() -> removes and returns the min value
+func (q *PriorityQueue[T]) Pop() (T, bool) {
+	return q.heap.PopMin()
+}
+
+// Peek() ->  returns the upcoming item without removing it.
+// ok is false when the queue is empty.
+func (q *PriorityQueue[T]) Peek() (T, bool) {
+	var zero T
+	if len(q.heap.Array) == 0 {
+		return zero, false
+	}
+	return q.heap.Array[0], true
+}
+
+// Size() -> return the Size of queue
+func (q PriorityQueue[T]) Size() int {
+	return len(q.heap.Array)
+}
+
+// Display() -> return the whole queue
+func (q PriorityQueue[T]) Display() []T {
+	return q.heap.Array
+}