diff --git a/Etage-Graph.cabal b/Etage-Graph.cabal
--- a/Etage-Graph.cabal
+++ b/Etage-Graph.cabal
@@ -1,5 +1,5 @@
 Name:                Etage-Graph
-Version:             0.1.1
+Version:             0.1.2
 Synopsis:            Data-flow based graph algorithms
 Description:         Data-flow based graph algorithms using the "Control.Etage" framework, showcasing its use for data-flow
                      computations. It is meant to be used with the "Data.Graph.Inductive" package which provides graph structures
@@ -38,11 +38,12 @@
   Build-depends:       base >= 4.3 && < 5,
                        fgl >= 5.4.2 && < 5.5,
                        random >= 1.0 && < 2,
+                       mtl >= 2.0 && < 3,
                        containers >= 0.4 && < 1,
                        deepseq >= 1.1 && < 2,
                        array >= 0.3 && < 1,
                        time >= 1.1 && < 2,
                        parallel >= 3.1 && < 4,
                        Etage == 0.1.8,
-                       Etage-Graph == 0.1.1
+                       Etage-Graph == 0.1.2
   GHC-options:         -Wall -rtsopts -threaded
diff --git a/src/Test.hs b/src/Test.hs
--- a/src/Test.hs
+++ b/src/Test.hs
@@ -9,12 +9,13 @@
 import Control.Exception
 import Control.Monad
 import Control.Monad.ST
+import Control.Monad.Trans
 import Control.Parallel.Strategies
 import Data.Array hiding (elems)
 import Data.Array.ST
 import Data.Data
 import Data.Graph.Etage
-import Data.Graph.Inductive hiding (edges, defaultGraphSize)
+import Data.Graph.Inductive hiding (defaultGraphSize)
 import qualified Data.Map as M
 import Data.List
 import Data.Maybe
@@ -77,13 +78,13 @@
 generateGraph graphSize = do
   when (graphSize < 1) $ throwIO $ AssertionFailed $ "Graph size out of bounds " ++ show graphSize
   let ns = map (\n -> (n, show n)) [1..graphSize]
-  edges <- fmap concat $ forM [1..graphSize] $ \node -> do
+  es <- fmap concat $ forM [1..graphSize] $ \node -> do
     nedges <- randomRIO (0, graphSize)
     others <- fmap (filter (node /=) . nub) $ forM [1..nedges] $ \_ -> randomRIO (1, graphSize)
     gen <- getStdGen
     let weights = randomRs (1, 10) gen
     return $ zip3 (repeat node) others weights
-  return $ mkGraph ns edges
+  return $ mkGraph ns es
 
 data TestNeuron a b = TestNeuron Int (Array (Node, Node) (b, [Node])) deriving (Typeable)
 
@@ -175,7 +176,7 @@
       writeFile outputDot $ graphviz graph "Etage" (8.27, 11.69) (1, 1) Landscape
     _                          -> return ()
   
-  putStrLn $ "Graph contains " ++ show graphSize ++ " nodes."
+  putStrLn $ "Graph contains " ++ show graphSize ++ " nodes and " ++ show (length . edges $ graph) ++ " edges."
   
   before <- getPOSIXTime
   let !paths = dijkstraShortestPaths graph graphSize `using` evalTraversable rdeepseq
@@ -184,8 +185,11 @@
 
   incubate $ do
     nerveTest <- (growNeuron :: NerveOnlyFor (TestNeuron String Double)) (\o -> o { graphSize, knownPaths = paths })
-    -- TODO: Also measure network growing time
+    before' <- liftIO getPOSIXTime
     pathsNerves <- shortestPaths graph
+    liftIO $ do
+      after' <- getPOSIXTime
+      putStrLn $ "Etage graph (external structure) growing time: " ++ show (after' - before')
     
     mapM_ (`attachTo` [TranslatableFor nerveTest]) $ M.elems pathsNerves
     
@@ -197,5 +201,5 @@
 dijkstraShortestPaths :: (Graph gr, Bounded b, Real b, NFData b) => gr a b -> Int -> Array (Node, Node) (b, [Node])
 dijkstraShortestPaths graph graphSize = array ((1, 1), (graphSize, graphSize)) $ initialValues ++ concat pathsValues
   where initialValues           = [ ((i, j), (maxBound, [])) | i <- [1..graphSize], j <- [1..graphSize] ]
-        pathsValues             = map spFromSource (nodes graph) `using` parListChunk (noNodes graph `div` (numCapabilities * 10)) rdeepseq
+        pathsValues             = map spFromSource (nodes graph) `using` parListChunk (max 1 $ noNodes graph `div` (numCapabilities * 10)) rdeepseq
         spFromSource sourceNode = map (\(LP (n@(node, len):ns)) -> ((sourceNode, node), (len, reverse . map fst $ n:ns))) $ spTree sourceNode graph