p2p, swarm, trie: avoid copying slices in loops (#17265)

3 files changed, 9 insertions, 9 deletions

diff --git a/p2p/discover/table.go b/p2p/discover/table.go
index 8803daa56..0a554bbeb 100644
--- a/p2p/discover/table.go
+++ b/p2p/discover/table.go
@@ -160,7 +160,7 @@ func (tab *Table) ReadRandomNodes(buf []*Node) (n int) {
 
 	// Find all non-empty buckets and get a fresh slice of their entries.
 	var buckets [][]*Node
-	for _, b := range tab.buckets {
+	for _, b := range &tab.buckets {
 		if len(b.entries) > 0 {
 			buckets = append(buckets, b.entries[:])
 		}
@@ -508,7 +508,7 @@ func (tab *Table) copyLiveNodes() {
 	defer tab.mutex.Unlock()
 
 	now := time.Now()
-	for _, b := range tab.buckets {
+	for _, b := range &tab.buckets {
 		for _, n := range b.entries {
 			if now.Sub(n.addedAt) >= seedMinTableTime {
 				tab.db.updateNode(n)
@@ -524,7 +524,7 @@ func (tab *Table) closest(target common.Hash, nresults int) *nodesByDistance {
 	// obviously correct. I believe that tree-based buckets would make
 	// this easier to implement efficiently.
 	close := &nodesByDistance{target: target}
-	for _, b := range tab.buckets {
+	for _, b := range &tab.buckets {
 		for _, n := range b.entries {
 			close.push(n, nresults)
 		}
@@ -533,7 +533,7 @@ func (tab *Table) closest(target common.Hash, nresults int) *nodesByDistance {
 }
 
 func (tab *Table) len() (n int) {
-	for _, b := range tab.buckets {
+	for _, b := range &tab.buckets {
 		n += len(b.entries)
 	}
 	return n
diff --git a/p2p/discv5/net_test.go b/p2p/discv5/net_test.go
index 001d193cc..1a8137673 100644
--- a/p2p/discv5/net_test.go
+++ b/p2p/discv5/net_test.go
@@ -355,7 +355,7 @@ func (tn *preminedTestnet) mine(target NodeID) {
 	fmt.Printf("	target: %#v,\n", tn.target)
 	fmt.Printf("	targetSha: %#v,\n", tn.targetSha)
 	fmt.Printf("	dists: [%d][]NodeID{\n", len(tn.dists))
-	for ld, ns := range tn.dists {
+	for ld, ns := range &tn.dists {
 		if len(ns) == 0 {
 			continue
 		}
diff --git a/p2p/discv5/table.go b/p2p/discv5/table.go
index c8d234b93..c793be508 100644
--- a/p2p/discv5/table.go
+++ b/p2p/discv5/table.go
@@ -81,7 +81,7 @@ func (tab *Table) chooseBucketRefreshTarget() common.Hash {
 	if printTable {
 		fmt.Println()
 	}
-	for i, b := range tab.buckets {
+	for i, b := range &tab.buckets {
 		entries += len(b.entries)
 		if printTable {
 			for _, e := range b.entries {
@@ -93,7 +93,7 @@ func (tab *Table) chooseBucketRefreshTarget() common.Hash {
 	prefix := binary.BigEndian.Uint64(tab.self.sha[0:8])
 	dist := ^uint64(0)
 	entry := int(randUint(uint32(entries + 1)))
-	for _, b := range tab.buckets {
+	for _, b := range &tab.buckets {
 		if entry < len(b.entries) {
 			n := b.entries[entry]
 			dist = binary.BigEndian.Uint64(n.sha[0:8]) ^ prefix
@@ -121,7 +121,7 @@ func (tab *Table) readRandomNodes(buf []*Node) (n int) {
 	// TODO: tree-based buckets would help here
 	// Find all non-empty buckets and get a fresh slice of their entries.
 	var buckets [][]*Node
-	for _, b := range tab.buckets {
+	for _, b := range &tab.buckets {
 		if len(b.entries) > 0 {
 			buckets = append(buckets, b.entries[:])
 		}
@@ -175,7 +175,7 @@ func (tab *Table) closest(target common.Hash, nresults int) *nodesByDistance {
 	// obviously correct. I believe that tree-based buckets would make
 	// this easier to implement efficiently.
 	close := &nodesByDistance{target: target}
-	for _, b := range tab.buckets {
+	for _, b := range &tab.buckets {
 		for _, n := range b.entries {
 			close.push(n, nresults)
 		}