Demo: coverage report comment for the go-coverage-report README

max_heap.go

@@ -83,6 +83,16 @@ func (h *MaxHeap) Items() []*Item {
 	return h.items
 }
 
+// Clone returns a copy of the queue which can be modified without affecting
+// the original queue.
+func (h *MaxHeap) Clone() *MaxHeap {
+	c := NewMaxHeap(len(h.items))
+	for _, item := range h.items {
+		c.items = append(c.items, &Item{ID: item.ID, Prio: item.Prio})
+	}
+	return c
+}
+
 // PopAndPush removes the item with the highest priority value and adds a new
 // value to the heap in one operation. This is faster than two separate calls
 // to Pop and Push.

min_heap.go

@@ -87,6 +87,16 @@ func (h *MinHeap) Items() []*Item {
 	return h.items
 }
 
+// Clone returns a copy of the queue which can be modified without affecting
+// the original queue.
+func (h *MinHeap) Clone() *MinHeap {
+	c := NewMinHeap(len(h.items))
+	for _, item := range h.items {
+		c.items = append(c.items, &Item{ID: item.ID, Prio: item.Prio})
+	}
+	return c
+}
+
 // PopAndPush removes the item with the lowest priority value and adds a new
 // value to the heap in one operation. This is faster than two separate calls
 // to Pop and Push.

topk/topk.go

@@ -1,5 +1,6 @@
 // Package topk selects the items with the lowest or highest priority from a
-// larger set of items using a bounded priority queue.
+// larger set of items using a bounded priority queue. This needs O(n log k)
+// time and O(k) memory instead of sorting all n items.
 package topk
 
 import "github.com/fgrosse/prioqueue"

topk/topk_test.go

@@ -19,3 +19,13 @@ func TestSmallest(t *testing.T) {
 	expected := []prioqueue.Item{{ID: 2, Prio: 1}, {ID: 4, Prio: 3}}
 	assert.Equal(t, expected, Smallest(items, 2))
 }
+
+func TestLargest(t *testing.T) {
+	expected := []prioqueue.Item{{ID: 5, Prio: 9}, {ID: 3, Prio: 8}, {ID: 1, Prio: 5}}
+	assert.Equal(t, expected, Largest(items, 3))
+}
+
+func TestInvalidK(t *testing.T) {
+	assert.Nil(t, Smallest(items, 0))
+	assert.Nil(t, Largest(items, -1))
+}