fix(guide): restructure curriculum guide articles (#36501)

* fix: restructure certifications guide articles
* fix: added 3 dashes line before prob expl
* fix: added 3 dashes line before hints
* fix: added 3 dashes line before solutions

guide/english/certifications/coding-interview-prep/data-structures/breadth-first-search/index.md

@@ -1,56 +1,46 @@
 ---
 title: Breadth-First Search
 ---
-## Breadth-First Search
+# Breadth-First Search
 
-Let's first define the `Tree` class to be used for the implementation of the Breadth First Search algorithm. 
 
-```python
-class Tree:
-  def __init__(self, x):
-    self.val = x
-    self.left = None
-    self.right = None
+---
+## Solutions
+
+<details><summary>Solution 1 (Click to Show/Hide)</summary>
+
+```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;
+  }
+  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;
+}
 ```
-
-The breadth first search algorithm moves from one level to another starting from the root of the tree. We will make use of a `queue` for this. 
-
-```python
-
-def bfs(root_node):
-  queue = [root_node]
-  
-  while queue:
-    top_element = queue.pop()
-    print("Node processed: ",top_element)
-    
-    if top_element.left:
-      queue.append(top_element.left)
-
-    if top_element.right:
-      queue.append(top_element.right)
-``` 
-
-We can easily modify the above code to print the level of each node as well.
-
-```python
-
-def bfs(root_node):
-  queue = [(root_node, 0)]
-  
-  while queue:
-    top_element, level = queue.pop()
-    print("Node processed: {} at level {}".format(top_element, level))
-    
-    if top_element.left:
-      queue.append((top_element.left, level + 1))
-
-    if top_element.right:
-      queue.append((top_element.right, level + 1))
-```
-
-
-| Complexity   | Time | Space |
-| ----- | ------ | ------ | 
-| BFS |   n    |    n   |  
-
+</details>