diff --git a/DAS/requirements.txt b/DAS/requirements.txt
index d0bb457..da7dcc7 100644
--- a/DAS/requirements.txt
+++ b/DAS/requirements.txt
@@ -1,3 +1,7 @@
 bitarray==2.6.0
-DAS==0.28.7
+DAS==0.29.0
+dicttoxml==1.7.16
+matplotlib==3.6.2
 networkx==3.0
+numpy==1.23.5
+seaborn==0.12.2
diff --git a/DAS/results.py b/DAS/results.py
index e20cdec..0efe26d 100644
--- a/DAS/results.py
+++ b/DAS/results.py
@@ -39,11 +39,6 @@ class Result:
         resXml = dicttoxml(resd1)
         xmlstr = minidom.parseString(resXml)
         xmlPretty = xmlstr.toprettyxml()
-        filePath = "results/"+execID+"/nbv-"+str(self.shape.numberValidators)+\
-                "-bs-"+str(self.shape.blockSize)+\
-                "-nd-"+str(self.shape.netDegree)+\
-                "-fr-"+str(self.shape.failureRate)+\
-                "-chi-"+str(self.shape.chi)+\
-                "-r-"+str(self.shape.run)+".xml"
+        filePath = "results/"+execID+"/"+str(self.shape)+".xml"
         with open(filePath, "w") as f:
             f.write(xmlPretty)
diff --git a/DAS/shape.py b/DAS/shape.py
index 2f99ebf..1dd19b2 100644
--- a/DAS/shape.py
+++ b/DAS/shape.py
@@ -11,7 +11,20 @@ class Shape:
         self.failureRate = failureRate
         self.netDegree = netDegree
         self.chi = chi
+        self.randomSeed = ""
 
+    def __repr__(self):
+        """Returns a printable representation of the shape"""
+        shastr = ""
+        shastr += "bs-"+str(self.blockSize)
+        shastr += "-nbv-"+str(self.numberValidators)
+        shastr += "-fr-"+str(self.failureRate)
+        shastr += "-chi-"+str(self.chi)
+        shastr += "-nd-"+str(self.netDegree)
+        shastr += "-r-"+str(self.run)
+        return shastr
 
-
+    def setSeed(self, seed):
+        """Adds the random seed to the shape"""
+        self.randomSeed = seed
 
diff --git a/config_example.py b/config_example.py
index c2f7fcf..248a8e9 100644
--- a/config_example.py
+++ b/config_example.py
@@ -39,11 +39,15 @@ blockSizes = range(32,65,16)
 # Per-topic mesh neighborhood size
 netDegrees = range(6, 9, 2)
 
-# number of rows and columns a validator is interested in
+# Number of rows and columns a validator is interested in
 chis = range(4, 9, 2)
 
+# Set to True if you want your run to be deterministic, False if not
 deterministic = False
 
+# If your run is deterministic you can decide the random seed. This is ignore otherwise.
+randomSeed = "DAS"
+
 def nextShape():
     for run in runs:
         for fr in failureRates:
diff --git a/study.py b/study.py
index f557fc2..e24fb46 100644
--- a/study.py
+++ b/study.py
@@ -13,8 +13,9 @@ from DAS import *
 # and https://github.com/joblib/joblib/issues/1017
 
 def runOnce(sim, config, shape):
-    if not config.deterministic:
-        random.seed(datetime.now())
+    if config.deterministic:
+        shape.setSeed(config.randomSeed+"-"+str(shape))
+        random.seed(shape.randomSeed)
 
     sim.initLogger()
     sim.resetShape(shape)
@@ -49,10 +50,7 @@ def study():
 
     sim.logger.info("Starting simulations:", extra=sim.format)
     start = time.time()
-
     results = Parallel(config.numJobs)(delayed(runOnce)(sim, config, shape) for shape in config.nextShape())
-
-
     end = time.time()
     sim.logger.info("A total of %d simulations ran in %d seconds" % (len(results), end-start), extra=sim.format)
 
@@ -61,8 +59,7 @@ def study():
             res.dump(execID)
         sim.logger.info("Results dumped into results/%s/" % (execID), extra=sim.format)
 
-    visualization = 1
-    if visualization:
+    if config.visualization:
         vis = Visualizer(execID)
         vis.plotHeatmaps()