diff --git a/vorlesung/L05_binaere_baeume/analyze_avl_tree.py b/vorlesung/L05_binaere_baeume/analyze_avl_tree.py
index 68b75d7..2dd72ce 100644
--- a/vorlesung/L05_binaere_baeume/analyze_avl_tree.py
+++ b/vorlesung/L05_binaere_baeume/analyze_avl_tree.py
@@ -4,19 +4,23 @@ from vorlesung.L05_binaere_baeume.avl_tree import AVLTree
 
 
 def analyze_complexity(sizes):
+    import random
+    sizes = list(sizes)
+    elements = random.sample(range(max(sizes) * 10), max(sizes))
     ctx = AlgoContext()
+    tree = AVLTree(ctx)
+    prev = 0
     for size in sizes:
-        z = Array.random(size, -100, 100, ctx)
-        tree = AVLTree(ctx)
-        for i in range(size - 1):
-            tree.insert(z[i].value)
+        for i in range(prev, size - 1):
+            tree.insert(elements[i])
         ctx.reset()
-        tree.insert(z[size - 1].value)
+        tree.insert(elements[size - 1])
         ctx.save_stats(size)
+        prev = size
 
     ctx.plot_stats(["comparisons"])
 
 
 if __name__ == "__main__":
-    sizes = range(1, 1001, 2)
+    sizes = range(10, 501, 10)
     analyze_complexity(sizes)
diff --git a/vorlesung/L05_binaere_baeume/analyze_binary_tree.py b/vorlesung/L05_binaere_baeume/analyze_binary_tree.py
index 3089c8a..f66bb53 100644
--- a/vorlesung/L05_binaere_baeume/analyze_binary_tree.py
+++ b/vorlesung/L05_binaere_baeume/analyze_binary_tree.py
@@ -4,19 +4,25 @@ from vorlesung.L05_binaere_baeume.bin_tree import BinaryTree
 
 
 def analyze_complexity(sizes):
+    import random
+    sizes = list(sizes)
+    # Alle Elemente vorab erzeugen – Baum wird inkrementell aufgebaut statt
+    # für jede Größe neu, dadurch O(n log n) statt O(n²) Gesamtaufwand.
+    elements = random.sample(range(max(sizes) * 10), max(sizes))
     ctx = AlgoContext()
+    tree = BinaryTree(ctx)
+    prev = 0
     for size in sizes:
-        z = Array.random(size, -100, 100, ctx)
-        tree = BinaryTree(ctx)
-        for i in range(size - 1):
-            tree.insert(z[i].value)
+        for i in range(prev, size - 1):   # Warm-up: ohne Messung einfügen
+            tree.insert(elements[i])
         ctx.reset()
-        tree.insert(z[size - 1].value)
+        tree.insert(elements[size - 1])   # gemessener Insert
         ctx.save_stats(size)
+        prev = size
 
     ctx.plot_stats(["comparisons"])
 
 
 if __name__ == "__main__":
-    sizes = range(1, 1001, 2)
+    sizes = range(10, 501, 10)
     analyze_complexity(sizes)
diff --git a/vorlesung/L05_binaere_baeume/bin_tree.py b/vorlesung/L05_binaere_baeume/bin_tree.py
index fad9520..11f4a01 100644
--- a/vorlesung/L05_binaere_baeume/bin_tree.py
+++ b/vorlesung/L05_binaere_baeume/bin_tree.py
@@ -42,7 +42,7 @@ class BinaryTree:
     def search(self, value):
         current = self.root
         value = self.new_node(value)
-        while current:
+        while current is not None:
             if value < current:
                 current = current.left
             elif value > current:
diff --git a/vorlesung/L05_binaere_baeume/bin_tree_node.py b/vorlesung/L05_binaere_baeume/bin_tree_node.py
index 8768dff..945900b 100644
--- a/vorlesung/L05_binaere_baeume/bin_tree_node.py
+++ b/vorlesung/L05_binaere_baeume/bin_tree_node.py
@@ -16,8 +16,8 @@ class BinaryTreeNode(Int):
         self.right = None
 
     def height(self):
-        left_height  = self.left.height()  if self.left  else 0
-        right_height = self.right.height() if self.right else 0
+        left_height  = self.left.height()  if self.left  is not None else 0
+        right_height = self.right.height() if self.right is not None else 0
         return 1 + max(left_height, right_height)
 
     def __repr__(self):