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Update breadth-first-search.english.md (#18900)

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Franklin Wang
2018-10-13 16:28:59 -07:00
committed by Jonathan Grah
parent ec7c3ced0e
commit e6402d3d6f
1 changed files with 32 additions and 31 deletions
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curriculum/challenges/english/08-coding-interview-prep/data-structures/breadth-first-search.english.md
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@ -8,7 +8,7 @@ challengeType: 1
<section id='description'>
So far, we've learned different ways of creating representations of graphs. What now? One natural question to have is what are the distances between any two nodes in the graph? Enter <dfn>graph traversal algorithms</dfn>.
<dfn>Traversal algorithms</dfn> are algorithms to traverse or visit nodes in a graph. One type of traversal algorithm is the breadth-first search algorithm.
This algorithm starts at one node, first visits all its neighbors that are one edge away, then goes on to visiting each of their neighbors.
This algorithm starts at one node, first visits all its neighbors that are one edge away, then goes on to visiting each of their neighbors and so on until all nodes have been reached.
Visually, this is what the algorithm is doing.
<img class='img-responsive' src='https://camo.githubusercontent.com/2f57e6239884a1a03402912f13c49555dec76d06/68747470733a2f2f75706c6f61642e77696b696d656469612e6f72672f77696b6970656469612f636f6d6d6f6e732f342f34362f416e696d617465645f4246532e676966'>
To implement this algorithm, you'll need to input a graph structure and a node you want to start at.
@ -83,36 +83,37 @@ console.info('after the test');
```js
function bfs(graph, root) {
// Distance object returned
var nodesLen = {};
// Set all distances to infinity
for (var i = 0; i < graph.length; i++) {
nodesLen[i] = Infinity;
// Distance object returned
var nodesLen = {};
// Set all distances to infinity
for (var i = 0; i < graph.length; i++) {
nodesLen[i] = Infinity;
}
nodesLen[root] = 0; // ...except root node
var queue = [root]; // Keep track of nodes to visit
var current; // Current node traversing
// Keep on going until no more nodes to traverse
while (queue.length !== 0) {
current = queue.shift();
// Get adjacent nodes from current node
var curConnected = graph[current]; // Get layer of edges from current
var neighborIdx = []; // List of nodes with edges
var idx = curConnected.indexOf(1); // Get first edge connection
while (idx !== -1) {
neighborIdx.push(idx); // Add to list of neighbors
idx = curConnected.indexOf(1, idx + 1); // Keep on searching
}
// Loop through neighbors and get lengths
for (var j = 0; j < neighborIdx.length; j++) {
// Increment distance for nodes traversed
if (nodesLen[neighborIdx[j]] === Infinity) {
nodesLen[neighborIdx[j]] = nodesLen[current] + 1;
queue.push(neighborIdx[j]); // Add new neighbors to queue
}
}
}
return nodesLen;
}
nodesLen[root] = 0; // ...except root node
var queue = [root]; // Keep track of nodes to visit
var current; // Current node traversing
// Keep on going until no more nodes to traverse
while (queue.length !== 0) {
current = queue.shift();
// Get adjacent nodes from current node
var curConnected = graph[current]; // Get layer of edges from current
var neighborIdx = []; // List of nodes with edges
var idx = curConnected.indexOf(1); // Get first edge connection
while (idx !== -1) {
neighborIdx.push(idx); // Add to list of neighbors
idx = curConnected.indexOf(1, idx + 1); // Keep on searching
}
// Loop through neighbors and get lengths
for (var j = 0; j < neighborIdx.length; j++) {
// Increment distance for nodes traversed
if (nodesLen[neighborIdx[j]] === Infinity) {
nodesLen[neighborIdx[j]] = nodesLen[current] + 1;
queue.push(neighborIdx[j]); // Add new neighbors to queue
}
}
}
return nodesLen;}
```
</section>
</section>