Sum of Left Leaves
Let’s solve this problem by using a depth-first search (DFS) approach, where we traverse the tree and whenever we find a left leaf node, we add its value to our sum. We define a helper function dfs
to do this recursive traversal.
Here is the Python solution:
|
|
This solution works as follows:
The
dfs
function traverses the tree. It takes two arguments: the current node, and a booleanis_left
indicating whether the node is a left child.If the node is
None
, we return 0.If the node is a left leaf (i.e.,
is_left
is True, and the node has no children), we return the node’s value.Otherwise, we recursively call
dfs
on the node’s left and right children. For the left child, we passTrue
foris_left
; for the right child, we passFalse
.We call
dfs
on the root of the tree, passingFalse
foris_left
since the root is not a left child.
|
|
Problem Classification
Binary Tree: The problem deals with operations on a binary tree, which is a data structure with a node-based hierarchy.
Tree Traversal: The task involves traversing through the binary tree, visiting each node to assess if it’s a left leaf.
Summation: The problem requires summing up values of certain nodes in the binary tree.
Leaves Identification: The problem involves identifying leaf nodes in the binary tree.
Positioning: The problem involves determining the position of nodes in a binary tree, specifically identifying nodes that are left children of their parent nodes.
Language Agnostic Coding Drills
Understanding Tree Structure: The first step is to comprehend the structure of a binary tree, with the root node, left child, and right child.
Understanding Null or Empty Nodes: Learn how to check whether a node in a tree is null or empty.
Understanding Leaf Nodes: Understand what a leaf node is, i.e., a node with no children.
Tree Traversal: Understand how to traverse a tree. In this case, a depth-first search approach is being used, going from root to the left and right nodes recursively.
Recursive Function: Understand how to write a recursive function that can traverse through the tree. Recursive functions call themselves with modified arguments until a base condition is met.
Position Checking: Understand how to check if a node is the left child of another node. In this case, it checks whether
root.left
exists and whetherroot.left
itself doesn’t have any children.Adding Values: Learn how to add values in a data structure, in this case, the values of the left leaf nodes.
The problem-solving approach for this problem would be:
Start by checking if the root of the tree is null or not. If it is null, return 0.
Next, check if the left child of the root exists and if it is a leaf node (it doesn’t have left or right children). If it is, add its value to the recursive call for the right child of the root.
If the left child of the root is not a leaf node, call the function recursively for both the left and right children of the root, adding their results.
The function eventually returns the sum of the values of all left leaves in the binary tree. The recursion ensures all nodes in the tree are visited, and the conditions within the function ensure that only left leaf nodes are considered in the sum.
Targeted Drills in Python
Please note that in real scenarios these drills would need a proper binary tree to function. For simplicity, we’ll represent tree nodes as lists, with the first element being the node value, the second element being the left child, and the third element being the right child.
- Understanding Tree Structure
|
|
- Understanding Null or Empty Nodes
|
|
- Understanding Leaf Nodes
|
|
- Tree Traversal
|
|
- Recursive Function
|
|
- Position Checking
|
|
- Adding Values
|
|
All these drills contribute to understanding and solving the problem, and they build upon each other. The final solution integrates all these concepts.