Renamed some files to more acuratly represent what they are.

book.json

@@ -134,7 +134,7 @@
         },
         {
           "lang": "lisp",
-          "name": "Lisp"
+          "name": "Common Lisp"
         },
         {
           "lang": "nim",

contents/bogo_sort/bogo_sort.md

@@ -58,7 +58,7 @@ In code, it looks something like this:
 {% sample lang="asm-x64" %}
 [import:93-113, lang:"asm-x64"](code/asm-x64/bogosort.s)
 {% sample lang="lisp" %}
-[import:20-24, lang:"lisp"](code/lisp/bogo-sort.lisp)
+[import:20-24, lang:"lisp"](code/clisp/bogo-sort.lisp)
 {% endmethod %}
 
 That's it.
@@ -116,7 +116,7 @@ We are done here!
 {% sample lang="asm-x64" %}
 [import, lang:"asm-x64"](code/asm-x64/bogosort.s)
 {% sample lang="lisp" %}
-[import, lang:"lisp"](code/lisp/bogo-sort.lisp)
+[import, lang:"lisp"](code/clisp/bogo-sort.lisp)
 {% endmethod %}
 
 

contents/bubble_sort/bubble_sort.md

@@ -49,7 +49,7 @@ This means that we need to go through the vector $$\mathcal{O}(n^2)$$ times with
 {% sample lang="php" %}
 [import:3-15, lang:"php"](code/php/bubble_sort.php)
 {% sample lang="lisp" %}
-[import:3-28, lang:"lisp"](code/lisp/bubble_sort.lisp)
+[import:3-28, lang:"lisp"](code/clisp/bubble_sort.lisp)
 {% sample lang="nim" %}
 [import:5-9, lang:"nim"](code/nim/bubble_sort.nim)
 {% sample lang="st" %}
@@ -120,7 +120,7 @@ Trust me, there are plenty of more complicated algorithms that do precisely the
 {% sample lang="php" %}
 [import, lang:"php"](code/php/bubble_sort.php)
 {% sample lang="lisp" %}
-[import, lang:"lisp"](code/lisp/bubble_sort.lisp)
+[import, lang:"lisp"](code/clisp/bubble_sort.lisp)
 {% sample lang="nim" %}
 [import, lang:"nim"](code/nim/bubble_sort.nim)
 {% sample lang="asm-x64" %}

contents/euclidean_algorithm/euclidean_algorithm.md

@@ -18,7 +18,7 @@ The algorithm is a simple way to find the *greatest common divisor* (GCD) of two
 {% sample lang="js" %}
 [import:15-29, lang="javascript"](code/javascript/euclidean_example.js)
 {% sample lang="lisp" %}
-[import:3-12, lang="lisp"](code/lisp/euclidean_algorithm.lisp)
+[import:3-12, lang="lisp"](code/clisp/euclidean_algorithm.lisp)
 {% sample lang="py" %}
 [import:11-22, lang="python"](code/python/euclidean_example.py)
 {% sample lang="haskell" %}
@@ -87,7 +87,7 @@ Modern implementations, though, often use the modulus operator (%) like so
 {% sample lang="js" %}
 [import:1-13, lang="javascript"](code/javascript/euclidean_example.js)
 {% sample lang="lisp" %}
-[import:13-17, lang="lisp"](code/lisp/euclidean_algorithm.lisp)
+[import:13-17, lang="lisp"](code/clisp/euclidean_algorithm.lisp)
 {% sample lang="py" %}
 [import:1-9, lang="python"](code/python/euclidean_example.py)
 {% sample lang="haskell" %}
@@ -161,7 +161,7 @@ The Euclidean Algorithm is truly fundamental to many other algorithms throughout
 {% sample lang="js" %}
 [import, lang="javascript"](code/javascript/euclidean_example.js)
 {% sample lang="lisp" %}
-[import, lang="lisp"](code/lisp/euclidean_algorithm.lisp)
+[import, lang="lisp"](code/clisp/euclidean_algorithm.lisp)
 {% sample lang="py" %}
 [import, lang="python"](code/python/euclidean_example.py)
 {% sample lang="haskell" %}

contents/jarvis_march/jarvis_march.md

@@ -41,7 +41,7 @@ Since this algorithm, there have been many other algorithms that have advanced t
 {% sample lang="cpp" %}
 [import, lang:"c_cpp"](code/c++/jarvis_march.cpp)
 {% sample lang="lisp" %}
-[import, lang:"lisp"](code/lisp/jarvis-march.lisp)
+[import, lang:"lisp"](code/clisp/jarvis-march.lisp)
 {% sample lang="java" %}
 [import, lang:"java"](code/java/JarvisMarch.java)
 {% sample lang="go" %}

contents/monte_carlo_integration/monte_carlo_integration.md

@@ -84,7 +84,7 @@ each point is tested to see whether it's in the circle or not:
 {% sample lang="scala" %}
 [import:3-3, lang:"scala"](code/scala/monte_carlo.scala)
 {% sample lang="lisp" %}
-[import:3-5, lang:"lisp"](code/scala/monte-carlo.lisp)
+[import:3-5, lang:"lisp"](code/clisp/monte-carlo.lisp)
 {% sample lang="asm-x64" %}
 [import:21-32, lang:"asm-x64"](code/asm-x64/monte_carlo.s)
 {% endmethod %}
@@ -170,7 +170,7 @@ Feel free to submit your version via pull request, and thanks for reading!
 {% sample lang="scala" %}
 [import, lang:"scala"](code/scala/monte_carlo.scala)
 {% sample lang="lisp" %}
-[import, lang:"lisp"](code/scala/monte-carlo.lisp)
+[import, lang:"lisp"](code/clisp/monte-carlo.lisp)
 {% sample lang="asm-x64" %}
 [import, lang:"asm-x64"](code/asm-x64/monte_carlo.s)
 {% endmethod %}