diff --git a/src/main/scala/com/nsrddyn/ALU/Prime.scala b/src/main/scala/com/nsrddyn/ALU/Prime.scala
index 343dcee..1432c93 100644
--- a/src/main/scala/com/nsrddyn/ALU/Prime.scala
+++ b/src/main/scala/com/nsrddyn/ALU/Prime.scala
@@ -28,12 +28,13 @@ class Prime() extends Benchmark {
   def isPrime(n: Int): Boolean = {
     if n <= 1 then false
     else !(2 to math.sqrt(n).toInt).exists(i => n % i  == 0)
+
+
   }
 
   def run(n: Int, result: Boolean): Unit = {
 
     for i <- 0 to n do if isPrime(i) == result then println("true") else println("false") 
-    
   }
 
 
diff --git a/src/main/scala/com/nsrddyn/FPU/CholeskyDecomposition.scala b/src/main/scala/com/nsrddyn/FPU/CholeskyDecomposition.scala
index b42ade9..80a1778 100644
--- a/src/main/scala/com/nsrddyn/FPU/CholeskyDecomposition.scala
+++ b/src/main/scala/com/nsrddyn/FPU/CholeskyDecomposition.scala
@@ -1,5 +1,8 @@
 package com.nsrddyn.fpu
 
+import scala.math._
+import scala.collection.immutable.ListSet
+import scala.collection.mutable.ArrayBuffer
 
 class CholeskyDecomposition {
 
@@ -13,14 +16,38 @@ class CholeskyDecomposition {
    *  Linpack uses the cholesky decomposition
    *  https://www.netlib.org/linpack/
    *
+   *  https://www.geeksforgeeks.org/dsa/cholesky-decomposition-matrix-decomposition/
    *
+   *  The Cholesky decomposition maps matrix A into the product of A = L · LH where L is the lower triangular matrix and LH is the transposed,
+   *  complex conjugate or Hermitian, and therefore of upper triangular form (Fig. 13.6).
+   *  This is true because of the special case of A being a square, conjugate symmetric matrix. 
    */ 
 
-  def choleskyDecomposition(n: Int): Unit =   {
+  def run(matrix: List[List[Int]]): Unit = {
 
-    for (w <- 0 to n) {
+    val n: Int = matrix.size
+
+    // store the lower triangular matrix
+    val lower = Vector[Vector[Int]]()
 
 
+    for (i <- 0 until n)
+    {
+      for (j <- 0 until i)
+        var sum: Double = 0
+
+        if j == i then
+        sum += math.pow(lowerBuffer(i)(j), 2)
+
+        end if 
+        lower(i)(j) = (sqrt(matrix(i)(j))())
+
+        j += 1
     }
+    i += 1
   }
+  
+  def (matrix: Vector[Vector[Int]], index: int, jindex: int ): Int = if j == 1 then return math.pow(matrix(index)(jindex)) else 
+
+
 }
diff --git a/src/main/scala/com/nsrddyn/Main.scala b/src/main/scala/com/nsrddyn/Main.scala
index de4fa1b..8d0ad7f 100644
--- a/src/main/scala/com/nsrddyn/Main.scala
+++ b/src/main/scala/com/nsrddyn/Main.scala
@@ -1,16 +1,23 @@
 package com.nsrddyn
 
+import com.nsrddyn.fpu.CholeskyDecomposition
+import com.nsrddyn.Tests.CholeskyDecompositionTest
+import java.time.Instant
+import com.nsrddyn.alu.*
+import com.nsrddyn.tools.Benchmark
+
 object Torque {
 
-  import java.time.Instant
-  import com.nsrddyn.alu.*
-  import com.nsrddyn.tools.Benchmark
-
-  @main def main(args: String*): Unit = 
+  println("hello world")
 
+  @main def main(args: String*): Unit =  {
     // ANSI ESCAPE CODE: clear screen
     println("\u001b[2J\u001b[H")
     println("--- TORQUE STRESS TESTING UTILITY ---")
 
-    }
+    var tester: CholeskyDecompositionTest = new CholeskyDecompositionTest
+    println(tester.test())
+
+  }
+}
 
diff --git a/src/main/scala/com/nsrddyn/Tests/CholeskyDecompositionTest.scala b/src/main/scala/com/nsrddyn/Tests/CholeskyDecompositionTest.scala
new file mode 100644
index 0000000..340caa3
--- /dev/null
+++ b/src/main/scala/com/nsrddyn/Tests/CholeskyDecompositionTest.scala
@@ -0,0 +1,16 @@
+package com.nsrddyn.Tests
+
+import com.nsrddyn.fpu.CholeskyDecomposition
+import scala.collection.immutable.ListSet
+
+class CholeskyDecompositionTest extends CholeskyDecomposition {
+
+  def test(): Unit = {
+
+    val cdp: CholeskyDecomposition = new  CholeskyDecomposition
+    val matrix: List[List[Int]] = List.empty[List[Int]]
+
+    println(cdp.run(matrix))
+
+  }
+}