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Shortest Path in Graph | Practice
Breadth First Search
course content

Conteúdo do Curso

Breadth First Search

Breadth First Search

1. What is BFS
2. Practice
3. Improve Your Code
4. Solving the Problems using BFS

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].

Tarefa

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.

Tarefa

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.

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Seção 2. Capítulo 3
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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].

Tarefa

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.

Tarefa

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 2. Capítulo 3
toggle bottom row

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].

Tarefa

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.

Tarefa

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

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].

Tarefa

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 2. Capítulo 3
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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