Course Content

Breadth First Search

1. What is BFS

How to Search Graph Class Implementation

2. Practice

Breadth First Traverse Check if is One Component Shortest Path in Graph Restoring Shortest Path Find All Connected Components Is a Tree

3. Improve Your Code

Congratulations Components Methods BFT and BFS

4. Solving the Problems using BFS

Coloring Pixels Shortest Clear Path

Shortest Path in Graph

BFS searching shortest path

Well done! Now, let's implement a method that helps us to find the length of shortest path between two vertices, i. e. minimum number of edges to reach end vertice from start.

You should store the length of the way from start to curr node, and you can do it by modifying visited array: visited[i] equals:

-1, if i not visited yet
0, if i is visited as first node
1, if i is a neighbor of node, that has mark 0
k, if i is a neighbor of node with mark k-1 etc.

This way, you'll store the distance between start and current node, like at the example:

So, the answer is a visited[end].

Task

bfs(start, end) returns a number of edges between start and end nodes. If there is no path, return -1.

Actually this method does traverse as BFT method, but until the end vertex is found. Copy & Paste your BFT algorithm, and add some changes.

Task

bfs(start, end) returns a number of edges between start and end nodes. If there is no path, return -1.

Actually this method does traverse as BFT method, but until the end vertex is found. Copy & Paste your BFT algorithm, and add some changes.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 2. Chapter 3

Shortest Path in Graph

BFS searching shortest path

Well done! Now, let's implement a method that helps us to find the length of shortest path between two vertices, i. e. minimum number of edges to reach end vertice from start.

You should store the length of the way from start to curr node, and you can do it by modifying visited array: visited[i] equals:

-1, if i not visited yet
0, if i is visited as first node
1, if i is a neighbor of node, that has mark 0
k, if i is a neighbor of node with mark k-1 etc.

This way, you'll store the distance between start and current node, like at the example:

So, the answer is a visited[end].

Task

bfs(start, end) returns a number of edges between start and end nodes. If there is no path, return -1.

Actually this method does traverse as BFT method, but until the end vertex is found. Copy & Paste your BFT algorithm, and add some changes.

Task

bfs(start, end) returns a number of edges between start and end nodes. If there is no path, return -1.

Actually this method does traverse as BFT method, but until the end vertex is found. Copy & Paste your BFT algorithm, and add some changes.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 2. Chapter 3

Shortest Path in Graph

BFS searching shortest path

Well done! Now, let's implement a method that helps us to find the length of shortest path between two vertices, i. e. minimum number of edges to reach end vertice from start.

You should store the length of the way from start to curr node, and you can do it by modifying visited array: visited[i] equals:

-1, if i not visited yet
0, if i is visited as first node
1, if i is a neighbor of node, that has mark 0
k, if i is a neighbor of node with mark k-1 etc.

This way, you'll store the distance between start and current node, like at the example:

So, the answer is a visited[end].

Task

bfs(start, end) returns a number of edges between start and end nodes. If there is no path, return -1.

Actually this method does traverse as BFT method, but until the end vertex is found. Copy & Paste your BFT algorithm, and add some changes.

Task

bfs(start, end) returns a number of edges between start and end nodes. If there is no path, return -1.

Actually this method does traverse as BFT method, but until the end vertex is found. Copy & Paste your BFT algorithm, and add some changes.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

BFS searching shortest path

Well done! Now, let's implement a method that helps us to find the length of shortest path between two vertices, i. e. minimum number of edges to reach end vertice from start.

You should store the length of the way from start to curr node, and you can do it by modifying visited array: visited[i] equals:

-1, if i not visited yet
0, if i is visited as first node
1, if i is a neighbor of node, that has mark 0
k, if i is a neighbor of node with mark k-1 etc.

This way, you'll store the distance between start and current node, like at the example:

So, the answer is a visited[end].

Task

bfs(start, end) returns a number of edges between start and end nodes. If there is no path, return -1.

Actually this method does traverse as BFT method, but until the end vertex is found. Copy & Paste your BFT algorithm, and add some changes.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 2. Chapter 3

Switch to desktop for real-world practiceContinue from where you are using one of the options below