Merge branch 'master' of github.com:algorithm-archivists/algorithm-archive

Author: leios

chapters/euclidean_algorithm/euclidean.md

@@ -26,7 +26,7 @@ The algorithm is a simple way to find the *greatest common divisor* (GCD) of two
 {% sample lang="java" %}
 [import:9-22, lang="java"](code/java/euclidean_example.java)
 {% sample lang="go" %}
-[import:25-38, lang="go"](code/go/euclidean.go)
+[import:25-38, lang="golang"](code/go/euclidean.go)
 {% endmethod %}
 
 Here, we simply line the two numbers up every step and subtract the lower value from the higher one every timestep. Once the two values are equal, we call that value the greatest common divisor. A graph of `a` and `b` as they change every step would look something like this:
@@ -59,7 +59,7 @@ Modern implementations, though, often use the modulus operator (%) like so
 {% sample lang="java" %}
 [import:24-35, lang="java"](code/java/euclidean_example.java)
 {% sample lang="go" %}
-[import:14-23, lang="go"](code/go/euclidean.go)
+[import:14-23, lang="golang"](code/go/euclidean.go)
 {% endmethod %}
 
 Here, we set `b` to be the remainder of `a%b` and `a` to be whatever `b` was last timestep. Because of how the modulus operator works, this will provide the same information as the subtraction-based implementation, but when we show `a` and `b` as they change with time, we can see that it might take many fewer steps:
@@ -108,7 +108,7 @@ Program.cs
 [import, lang="java"](code/java/euclidean_example.java)
 {% sample lang="go" %}
 ### Go
-[import, lang="go"](code/go/euclidean.go)
+[import, lang="golang"](code/go/euclidean.go)
 {% endmethod %}
 
 

chapters/monte_carlo/monte_carlo.md

@@ -46,9 +46,9 @@ each point is tested to see whether it's in the circle or not:
 {% sample lang="rs" %}
 [import:7-9, lang:"rust"](code/rust/monte_carlo.rs)
 {% sample lang="d" %}
-[import:2-5, lang:"d"](code/rust/monte_carlo.d)
+[import:2-5, lang:"d"](code/d/monte_carlo.d)
 {% sample lang="go" %}
-[import:12-14, lang:"go"](code/go/monteCarlo.go)
+[import:12-14, lang:"golang"](code/go/monteCarlo.go)
 {% endmethod %}
 
 If it's in the circle, we increase an internal count by one, and in the end,
@@ -97,7 +97,7 @@ Feel free to submit your version via pull request, and thanks for reading!
 [import, lang:"d"](code/d/monte_carlo.d)
 ### Go
 {%sample lang="go" %}
-[import, lang:"go"](code/go/monteCarlo.go)
+[import, lang:"golang"](code/go/monteCarlo.go)
 {% endmethod %}
 
 

chapters/sorting_searching/bubble/bubble_sort.md

@@ -31,7 +31,7 @@ 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:"go"](code/go/bubbleSort.go)
+[import:7-21, lang:"golang"](code/go/bubbleSort.go)
 {% sample lang="racket" %}
 [import:5-19, lang:"racket"](code/racket/bubbleSort.rkt)
 {% endmethod %}