diff --git a/cachematrix.R b/cachematrix.R
index a50be65aa44..00df4c3b87f 100644
--- a/cachematrix.R
+++ b/cachematrix.R
@@ -1,15 +1,42 @@
-## Put comments here that give an overall description of what your
-## functions do
+## This second programming assignment will require you to write an R function is able to cache
+## potentially time-consuming computations. For example, taking the mean of a numeric vector is
+## typically a fast operation. However, for a very long vector, it may take too long to compute 
+## the mean, especially if it has to be computed repeatedly (e.g. in a loop). If the contents of 
+## a vector are not changing, it may make sense to cache the value of the mean so that when we 
+## need it again, it can be looked up in the cache rather than recomputed. In this Programming 
+## Assignment will take advantage of the scoping rules of the R language and how they can be 
+## manipulated to preserve state inside of an R object.
 
-## Write a short comment describing this function
+## This function creates a special "matrix" object that can cache its inverse.
 
 makeCacheMatrix <- function(x = matrix()) {
-
+        m <- NULL
+        set <- function(y) {
+                x <<- y
+                m <<- NULL
+        }
+        get <- function() x
+        setInverse <- function(inverse) m <<- inverse
+        getInverse <- function() m
+        list(set = set, get = get,
+             setInverse = setInverse,
+             getInverse = getInverse)
 }
 
 
-## Write a short comment describing this function
+## This function computes the inverse of the special "matrix" returned by makeCacheMatrix above. 
+## If the inverse has already been calculated (and the matrix has not changed), then the cachesolve 
+## should retrieve the inverse from the cache.
 
 cacheSolve <- function(x, ...) {
         ## Return a matrix that is the inverse of 'x'
+        m <- getInverse()
+        if(!is.null(m)){
+                message("Checking cache...")
+                return(m)
+        }
+        data <- x$get()
+        m <- solve(data)
+        x$setInverse(m)
+        m
 }