src/main/scala/com/nsrddyn/ALU/Prime.scala

@@ -1,9 +1,9 @@
 package com.nsrddyn.alu
-import com.nsrddyn.alu.Prime
-import com.nsrddyn.tools.Benchmark
-import com.nsrddyn.test
 
-class Prime() extends  {
+
+import com.nsrddyn.tools.Benchmark
+
+class Prime() extends Benchmark {
 
   /*
    * Calculate all primes up to limit
@@ -40,25 +40,3 @@ class Prime() extends  {
 
 }
 
-
-
-
-class PrimeRunner extends Workload {
-
-  def run(threads: Int): Unit = {
-
-    val pr = new Prime()
-    val br = new Benchmark()
-
-    /*
-     * test cases
-     *
-     * 7919 true
-     * 2147483647 false
-     */
-
-    val time = pr.run(7919, true)
-    println(time)
-
-  } 
-}

src/main/scala/com/nsrddyn/Enums/Status.scala

@@ -0,0 +1,6 @@
+package com.nsrddyn.Enums
+
+enum Status:
+  case PASS 
+  case FAIL 
+

src/main/scala/com/nsrddyn/FPU/CholeskyDecomposition.scala

@@ -23,24 +23,31 @@ class CholeskyDecomposition {
    *  This is true because of the special case of A being a square, conjugate symmetric matrix. 
    */ 
 
-  def run(matrix: Vector[Vector[Int]]): Unit = {
+  def run(matrix: List[List[Int]]): Unit = {
 
-    val size: Int = matrix.size
-    val lower: ArrayBuffer[ArrayBuffer[Int]] = ArrayBuffer[ArrayBuffer[Int]]()
+    val n: Int = matrix.size
 
-    for 
-      i <- 0 to size 
-      j <- 0 until i 
-    do 
-      if i == j then lower(i)(j) = getSquaredSummation(lower, i, j, matrix) else lower(j)(j) = getReversedSummation(lower, i, j, matrix)
+    // 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
   }
   
-  private def getReversedSummation(lower: ArrayBuffer[ArrayBuffer[Int]], i: Int, j: Int, matrix: Vector[Vector[Int]]) = {
-    math.sqrt(matrix(j)(j) - (0 until j).map { k => lower(i)(k) * lower(j)(k) }.sum).toInt
-  }
-  private def getSquaredSummation(lower: ArrayBuffer[ArrayBuffer[Int]], i: Int, j: Int, matrix:  Vector[Vector[Int]]) = {
-    ((matrix(i)(j) - (0 until j).map { k => math.pow(lower(j)(k), 2)}.sum) / lower(j)(j)).toInt
-  }
-}
+  def (matrix: Vector[Vector[Int]], index: int, jindex: int ): Int = if j == 1 then return math.pow(matrix(index)(jindex)) else 
 
+
+}

src/main/scala/com/nsrddyn/Main.scala

@@ -6,11 +6,6 @@ import java.time.Instant
 import com.nsrddyn.alu.*
 import com.nsrddyn.tools.Benchmark
 
-enum Status:
-  case PASS 
-  case FAIL 
-
-
 object Torque {
 
   println("hello world")

src/main/scala/com/nsrddyn/Tests/CholeskyDecompositionTest.scala

@@ -8,12 +8,9 @@ class CholeskyDecompositionTest extends CholeskyDecomposition {
   def test(): Unit = {
 
     val cdp: CholeskyDecomposition = new  CholeskyDecomposition
-    val matrix: Vector[Vector[Int]] = Vector(Vector(1,2,3),Vector(1,2,3),Vector(1,2,3))
+    val matrix: List[List[Int]] = List.empty[List[Int]]
 
     println(cdp.run(matrix))
 
   }
-
-
-
 }

src/main/scala/com/nsrddyn/Tests/PrimeTest.scala

@@ -0,0 +1,29 @@
+package com.nsrddyn.Test
+
+import com.nsrddyn.alu.Prime
+import com.nsrddyn.tools.Benchmark
+
+class PrimeTest extends Prime {
+
+  def runBasic(): Unit = {
+
+    val pr = new Prime()
+    val br = new Benchmark()
+
+    /*
+     * test cases
+     *
+     * 7919 true
+     * 2147483647 false
+     */
+
+    val time = pr.run(7919, true)
+    println(time)
+
+  } 
+
+  def runExtreme(): Unit = println("running some very have stuff!")
+  
+
+
+}

src/main/scala/com/nsrddyn/Traits/Workload.scala

@@ -1,9 +0,0 @@
-package com.nsrddyn.Traits
-
-import zio._
-
-trait Workload {
-
-  def name: String
-  def run:  ZIO[Any, Nothing, Unit]
-}