change the name golang to go (#490)

Author: Julian

contents/bubble_sort/bubble_sort.md

@@ -35,7 +35,7 @@ This means that we need to go through the vector $$\mathcal{O}(n^2)$$ times with
 {% sample lang="d" %}
 [import:3-18, lang:"d"](code/d/bubble_sort.d)
 {% sample lang="go" %}
-[import:7-21, lang:"golang"](code/go/bubbleSort.go)
+[import:7-21, lang:"go"](code/go/bubbleSort.go)
 {% sample lang="racket" %}
 [import:6-19, lang:"scheme"](code/racket/bubbleSort.rkt)
 {% sample lang="swift" %}
@@ -104,7 +104,7 @@ Trust me, there are plenty of more complicated algorithms that do precisely the
 {% sample lang="d" %}
 [import, lang:"d"](code/d/bubble_sort.d)
 {% sample lang="go" %}
-[import, lang:"golang"](code/go/bubbleSort.go)
+[import, lang:"go"](code/go/bubbleSort.go)
 {% sample lang="racket" %}
 [import, lang:"scheme"](code/racket/bubbleSort.rkt)
 {% sample lang="swift" %}

contents/euclidean_algorithm/euclidean_algorithm.md

@@ -28,7 +28,7 @@ The algorithm is a simple way to find the *greatest common divisor* (GCD) of two
 {% sample lang="ml" %}
 [import:9-17, lang="ocaml"](code/ocaml/euclidean_example.ml)
 {% sample lang="go" %}
-[import:25-38, lang="golang"](code/go/euclidean.go)
+[import:25-38, lang="go"](code/go/euclidean.go)
 {% sample lang="swift" %}
 [import:1-14, lang="swift"](code/swift/euclidean_algorithm.swift)
 {% sample lang="matlab" %}
@@ -91,7 +91,7 @@ Modern implementations, though, often use the modulus operator (%) like so
 {% sample lang="ml" %}
 [import:3-7, lang="ocaml"](code/ocaml/euclidean_example.ml)
 {% sample lang="go" %}
-[import:14-23, lang="golang"](code/go/euclidean.go)
+[import:14-23, lang="go"](code/go/euclidean.go)
 {% sample lang="swift" %}
 [import:16-27, lang="swift"](code/swift/euclidean_algorithm.swift)
 {% sample lang="matlab" %}
@@ -159,7 +159,7 @@ The Euclidean Algorithm is truly fundamental to many other algorithms throughout
 {% sample lang="ml" %}
 [import, lang="ocaml"](code/ocaml/euclidean_example.ml)
 {% sample lang="go" %}
-[import, lang="golang"](code/go/euclidean.go)
+[import, lang="go"](code/go/euclidean.go)
 {% sample lang="swift" %}
 [import, lang="swift"](code/swift/euclidean_algorithm.swift)
 {% sample lang="matlab" %}

contents/monte_carlo_integration/monte_carlo_integration.md

@@ -54,7 +54,7 @@ each point is tested to see whether it's in the circle or not:
 {% sample lang="d" %}
 [import:2-5, lang:"d"](code/d/monte_carlo.d)
 {% sample lang="go" %}
-[import:12-14, lang:"golang"](code/go/monteCarlo.go)
+[import:12-14, lang:"go"](code/go/monteCarlo.go)
 {% sample lang="r" %}
 [import:2-6, lang:"r"](code/r/monte_carlo.R)
 {% sample lang="java" %}
@@ -129,7 +129,7 @@ Feel free to submit your version via pull request, and thanks for reading!
 {%sample lang="d" %}
 [import, lang:"d"](code/d/monte_carlo.d)
 {%sample lang="go" %}
-[import, lang:"golang"](code/go/monteCarlo.go)
+[import, lang:"go"](code/go/monteCarlo.go)
 {%sample lang="r" %}
 [import, lang:"r"](code/r/monte_carlo.R)
 {% sample lang="java" %}

contents/tree_traversal/tree_traversal.md

@@ -33,7 +33,7 @@ This has not been implemented in your chosen language, so here is the Julia code
 {% sample lang="crystal" %}
 [import:1-5, lang:"crystal"](code/crystal/tree-traversal.cr)
 {% sample lang="go" %}
-[import:5-8, lang:"golang"](code/golang/treetraversal.go)
+[import:5-8, lang:"go"](code/golang/treetraversal.go)
 {% endmethod %}
 
 Because of this, the most straightforward way to traverse the tree might be recursive. This naturally leads us to the Depth-First Search (DFS) method:
@@ -69,7 +69,7 @@ Because of this, the most straightforward way to traverse the tree might be recu
 {% sample lang="crystal" %}
 [import:7-10, lang:"crystal"](code/crystal/tree-traversal.cr)
 {% sample lang="go" %}
-[import:10-15, lang:"golang"](code/golang/treetraversal.go)
+[import:10-15, lang:"go"](code/golang/treetraversal.go)
 {% endmethod %}
 
 At least to me, this makes a lot of sense. We fight recursion with recursion! First, we first output the node we are on and then we call `DFS_recursive(...)` on each of its children nodes. This method of tree traversal does what its name implies: it goes to the depths of the tree first before going through the rest of the branches. In this case, the ordering looks like:
@@ -113,7 +113,7 @@ Now, in this case the first element searched through is still the root of the tr
 {% sample lang="crystal" %}
 [import:12-15, lang:"crystal"](code/crystal/tree-traversal.cr)
 {% sample lang="go" %}
-[import:17-22, lang:"golang"](code/golang/treetraversal.go)
+[import:17-22, lang:"go"](code/golang/treetraversal.go)
 {% endmethod %}
 
 <p>
@@ -152,7 +152,7 @@ In this case, the first node visited is at the bottom of the tree and moves up t
 {% sample lang="crystal" %}
 [import:17-31, lang:"crystal"](code/crystal/tree-traversal.cr)
 {% sample lang="go" %}
-[import:24-38, lang:"golang"](code/golang/treetraversal.go)
+[import:24-38, lang:"go"](code/golang/treetraversal.go)
 {% endmethod %}
 
 <p>
@@ -201,7 +201,7 @@ In code, it looks like this:
 {% sample lang="crystal" %}
 [import:33-41, lang:"crystal"](code/crystal/tree-traversal.cr)
 {% sample lang="go" %}
-[import:40-49, lang:"golang"](code/golang/treetraversal.go)
+[import:40-49, lang:"go"](code/golang/treetraversal.go)
 {% endmethod %}
 
 All this said, there are a few details about DFS that might not be idea, depending on the situation. For example, if we use DFS on an incredibly long tree, we will spend a lot of time going further and further down a single branch without searching the rest of the data structure. In addition, it is not the natural way humans would order a tree if asked to number all the nodes from top to bottom. I would argue a more natural traversal order would look something like this:
@@ -242,7 +242,7 @@ And this is exactly what Breadth-First Search (BFS) does! On top of that, it can
 {% sample lang="crystal" %}
 [import:43-51, lang:"crystal"](code/crystal/tree-traversal.cr)
 {% sample lang="go" %}
-[import:51-60, lang:"golang"](code/golang/treetraversal.go)
+[import:51-60, lang:"go"](code/golang/treetraversal.go)
 {% endmethod %}
 
 ## Example Code
@@ -285,7 +285,7 @@ The code snippets were taken from this [Scratch project](https://scratch.mit.edu
 {% sample lang="crystal" %}
 [import, lang:"crystal"](code/crystal/tree-traversal.cr)
 {% sample lang="go" %}
-[import, lang:"golang"](code/golang/treetraversal.go)
+[import, lang:"go"](code/golang/treetraversal.go)
 {% endmethod %}