autopilot/choice_test: add chooseN tests

autopilot/choice_test.go

@@ -0,0 +1,196 @@
+package autopilot
+
+import (
+	"encoding/binary"
+	"math/rand"
+	"reflect"
+	"testing"
+	"testing/quick"
+)
+
+var (
+	nID1 = NodeID([33]byte{1})
+	nID2 = NodeID([33]byte{2})
+	nID3 = NodeID([33]byte{3})
+	nID4 = NodeID([33]byte{4})
+)
+
+// TestChooseNEmptyMap checks that chooseN returns an empty result when no
+// nodes are chosen among.
+func TestChooseNEmptyMap(t *testing.T) {
+	t.Parallel()
+
+	nodes := map[NodeID]*AttachmentDirective{}
+	property := func(n uint32) bool {
+		res, err := chooseN(n, nodes)
+		if err != nil {
+			return false
+		}
+
+		// Result should always be empty.
+		return len(res) == 0
+	}
+
+	if err := quick.Check(property, nil); err != nil {
+		t.Fatal(err)
+	}
+}
+
+// candidateMapVarLen is a type we'll use to generate maps of various lengths
+// up to 255 to be used during QuickTests.
+type candidateMapVarLen map[NodeID]*AttachmentDirective
+
+// Generate generates a value of type candidateMapVarLen to be used during
+// QuickTests.
+func (candidateMapVarLen) Generate(rand *rand.Rand, size int) reflect.Value {
+	nodes := make(map[NodeID]*AttachmentDirective)
+
+	// To avoid creating huge maps, we restrict them to max uint8 len.
+	n := uint8(rand.Uint32())
+
+	for i := uint8(0); i < n; i++ {
+		s := rand.Float64()
+
+		// We set small values to zero, to ensure we handle these
+		// correctly.
+		if s < 0.01 {
+			s = 0
+		}
+
+		var nID [33]byte
+		binary.BigEndian.PutUint32(nID[:], uint32(i))
+		nodes[nID] = &AttachmentDirective{
+			Score: s,
+		}
+	}
+
+	return reflect.ValueOf(nodes)
+}
+
+// TestChooseNMinimum test that chooseN returns the minimum of the number of
+// nodes we request and the number of positively scored nodes in the given map.
+func TestChooseNMinimum(t *testing.T) {
+	t.Parallel()
+
+	// Helper to count the number of positive scores in the given map.
+	numPositive := func(nodes map[NodeID]*AttachmentDirective) int {
+		cnt := 0
+		for _, v := range nodes {
+			if v.Score > 0 {
+				cnt++
+			}
+		}
+		return cnt
+	}
+
+	// We use let the type of n be uint8 to avoid generating huge numbers.
+	property := func(nodes candidateMapVarLen, n uint8) bool {
+		res, err := chooseN(uint32(n), nodes)
+		if err != nil {
+			return false
+		}
+
+		positive := numPositive(nodes)
+
+		// Result should always be the minimum of the number of nodes
+		// we wanted to select and the number of positively scored
+		// nodes in the map.
+		min := positive
+		if int(n) < min {
+			min = int(n)
+		}
+
+		if len(res) != min {
+			return false
+
+		}
+		return true
+	}
+
+	if err := quick.Check(property, nil); err != nil {
+		t.Fatal(err)
+	}
+}
+
+// TestChooseNSample sanity checks that nodes are picked by chooseN according
+// to their scores.
+func TestChooseNSample(t *testing.T) {
+	t.Parallel()
+
+	const numNodes = 500
+	const maxIterations = 100000
+	fifth := uint32(numNodes / 5)
+
+	nodes := make(map[NodeID]*AttachmentDirective)
+
+	// we make 5 buckets of nodes: 0, 0.1, 0.2, 0.4 and 0.8 score. We want
+	// to check that zero scores never gets chosen, while a doubling the
+	// score makes a node getting chosen about double the amount (this is
+	// true only when n <<< numNodes).
+	j := 2 * fifth
+	score := 0.1
+	for i := uint32(0); i < numNodes; i++ {
+
+		// Each time i surpasses j we double the score we give to the
+		// next fifth of nodes.
+		if i >= j {
+			score *= 2
+			j += fifth
+		}
+		s := score
+
+		// The first 1/5 of nodes we give a score of 0.
+		if i < fifth {
+			s = 0
+		}
+
+		var nID [33]byte
+		binary.BigEndian.PutUint32(nID[:], i)
+		nodes[nID] = &AttachmentDirective{
+			Score: s,
+		}
+	}
+
+	// For each value of N we'll check that the nodes are picked the
+	// expected number of times over time.
+	for _, n := range []uint32{1, 5, 10, 20, 50} {
+		// Since choosing more nodes will result in chooseN getting
+		// slower we decrease the number of iterations. This is okay
+		// since the variance in the total picks for a node will be
+		// lower when choosing more nodes each time.
+		iterations := maxIterations / n
+		count := make(map[NodeID]int)
+		for i := 0; i < int(iterations); i++ {
+			res, err := chooseN(n, nodes)
+			if err != nil {
+				t.Fatalf("failed choosing nodes: %v", err)
+			}
+
+			for nID := range res {
+				count[nID]++
+			}
+		}
+
+		// Sum the number of times a node in each score bucket was
+		// picked.
+		sums := make(map[float64]int)
+		for nID, s := range nodes {
+			sums[s.Score] += count[nID]
+		}
+
+		// The count of each bucket should be about double of the
+		// previous bucket.  Since this is all random, we check that
+		// the result is within 20% of the expected value.
+		for _, score := range []float64{0.2, 0.4, 0.8} {
+			cnt := sums[score]
+			half := cnt / 2
+			expLow := half - half/5
+			expHigh := half + half/5
+			if sums[score/2] < expLow || sums[score/2] > expHigh {
+				t.Fatalf("expected the nodes with score %v "+
+					"to be chosen about %v times, instead "+
+					"was %v", score/2, half, sums[score/2])
+			}
+		}
+	}
+}