Learn and practice the Tree Depth-First Search and Tree Breadth-First Search patterns to solve coding interview problems.

Educative-99 in Python: Accelerate Your Coding Interview Prep

Trees play a pivotal role in organizing hierarchical data, optimizing searches, and solving complex problems. In this module, we’ll learn to choose the appropriate tree for a given problem and apply the more appropriate of the two major traversal techniques, breadth-first or depth-first, to solve it.

Trees

# Statement

Given two words, `src` and `dest`, and a list, `words`, return the number of words in the shortest transformation sequence from `src` to `dest`. If no such sequence can be formed, return $0$.

A **transformation sequence** is a sequence of words $($`src` $\to$  $word_1$ $\to$ $word_2$ $\to$ $word_3$ $...$ $\to$ $word_j$ $)$ that has the following properties:

- $word_j =$ `dest` 
- Every pair of consecutive words differs by a single character.
- All the words in the sequence are present in the `words`. The `src` does not need to be present in `words`.

**Constraints:**

- $1 \leq$ `src.length` $\leq 10$
- `src.length` $=$ `dest.length` $=$ `words[i].length`
- `src` $\neq$ `dest` 
- $1 \leq$ `words.length` $\leq 5000$


- No duplicates in the `words`
- `src`, `dest`, and `words[i]` consist of lowercase English characters.


# Examples

Word Ladder

Statement