26. Root-to-Leaf Paths
Backtracking algorithm collecting all paths from root node down to every terminal leaf node.
Live loop — open the studio to scrub, add your own array, or race it in Battle Arena.
Asked in interviews at
Reference implementation (Python)
def binary_tree_paths(root):
paths = []
def dfs(node, path):
if not node: return
path.append(str(node.val))
if not node.left and not node.right:
paths.append("->".join(path))
else:
dfs(node.left, path)
dfs(node.right, path)
path.pop()
dfs(root, [])
return pathsEmbed this visualization
Drop a live, looping 26. Root-to-Leaf Paths canvas into a blog post or course page.
<iframe src="/embed/tree-root-to-leaf" width="100%" height="380" style="border:1px solid #e6e8ec;border-radius:14px" loading="lazy" title="3D algorithm visualization by CodeWithMunnaX"></iframe>Frequently asked
What is the time and space complexity of 26. Root-to-Leaf Paths?
26. Root-to-Leaf Paths runs in O(n) time and O(h) auxiliary space.
Is the 26. Root-to-Leaf Paths visualizer free?
The core 3D visualizer, Web Audio chimes and step intuition are free. A one-time ₹49 Pro Pass unlocks advanced algorithms, large custom arrays, Battle Arena and reel export.
Which companies ask 26. Root-to-Leaf Paths in interviews?
26. Root-to-Leaf Paths shows up in interviews at Uber, Microsoft, DoorDash.
How does the 3D visualization of 26. Root-to-Leaf Paths work?
Each array value becomes a 3D pillar whose height maps to its value. Comparisons glow amber, swaps flash red, and settled elements lock green while a floating pointer badge tracks the active index — synchronized line-by-line with the Python code.