diff --git a/cachematrix.R b/cachematrix.R
index a50be65aa44..c41c93bcbe2 100644
--- a/cachematrix.R
+++ b/cachematrix.R
@@ -1,15 +1,61 @@
-## Put comments here that give an overall description of what your
-## functions do
-
-## Write a short comment describing this function
-
-makeCacheMatrix <- function(x = matrix()) {
-
-}
-
-
-## Write a short comment describing this function
-
-cacheSolve <- function(x, ...) {
-        ## Return a matrix that is the inverse of 'x'
-}
+## makeCacheMatrix is the function that returns a closure
+## that has methods initialize and retrieve matrix as wels as
+## to set and return an attribute that is an inverse of the matrix
+
+## Example: lets generate positive semi-definite random matrix:
+ # M <- matrix(rnorm(100),10, 10)
+ # M <- M %*% t(M)
+ 
+
+##
+
+## makeCacheMatrix is an object constructor, that initializes object with set 
+ # and return methods 
+
+makeCacheMatrix <- function(X = matrix()) {
+  myInverse<-NULL
+  
+  get <- function() X
+  #### get will return 
+  
+  set <- function(Y) {
+    #### set will set matrix in the defining environemnt
+    #### and will reset inverse to NULL in the parent env
+    X<<-Y
+    myInverse <<- NULL
+  }
+  
+  #### 'methods' for working with our "object"
+  setInv<- function(XInv) myInverse <<- XInv
+  
+  getInv <- function() myInverse
+  
+  #return list
+  list(get = get, set = set, getInv = getInv, setInv = setInv)
+
+}
+
+
+## cacheSolve returnsm inverse of the matrix 
+ # it can also cache a particular solution if additional parameters are passed
+ # to solve() via ...
+
+cacheSolve <- function(x, ...) {
+  #### Returns a matrix that is the inverse of 'x'
+  #### WE rely on this method to work correctly with our closure.
+  #### this approach is set up by the framework of this assignment. It differs
+  #### from object oriented paradigm in that this method is not encapsulated.
+  INV <- x$getInv()
+  
+  if (!is.null(INV)) {
+    message("returning cached data")
+    return(INV)
+  }
+  
+  MX <- x$get()
+  INV <- solve(MX, ...)
+  x$setInv(INV)
+  #returned inverted matrix
+  INV
+}
+
diff --git a/contact.md b/contact.md
new file mode 100644
index 00000000000..b573c339183
--- /dev/null
+++ b/contact.md
@@ -0,0 +1,4 @@
+Contact
+-------
+
+Should you want to contact me with regard to this assignment you can find me by spolgul on google.
diff --git a/example/example.R b/example/example.R
new file mode 100755
index 00000000000..b93069e9deb
--- /dev/null
+++ b/example/example.R
@@ -0,0 +1,32 @@
+makeVector <- function(x = numeric()) {
+  m <- NULL
+  set <- function(y) {
+    x <<- y
+    m <<- NULL
+  }
+  get <- function() x
+  setmean <- function(mean) m <<- mean
+  getmean <- function() m
+  list(set = set, get = get,
+       setmean = setmean,
+       getmean = getmean)
+}
+
+cachemean <- function(x, ...) {
+  m <- x$getmean()
+  if(!is.null(m)) {
+    message("getting cached data")
+    return(m)
+  }
+  data <- x$get()
+  m <- mean(data, ...)
+  x$setmean(m)
+  m
+}
+
+v<-rnorm(10e7)
+
+mv<-makeVector(v)
+
+mean1<-cachemean(mv)
+mean2<-vachemean(mv)
\ No newline at end of file
diff --git a/simpleTest.R b/simpleTest.R
new file mode 100755
index 00000000000..df5cb9b3ded
--- /dev/null
+++ b/simpleTest.R
@@ -0,0 +1,11 @@
+set.seed(1713)
+#M <- matrix(rnorm(100),10, 10)
+M <- matrix(runif(10e6),nrow=1000, ncol=1000)
+M <- M%*% t(M)
+dim(M)
+XObj <- makeCacheMatrix (M)
+#XObj$set(M)
+system.time(I1<-cacheSolve(XObj))
+# second run
+system.time(I2<-cacheSolve(XObj))
+