diff --git a/examples/UGM_chain.cpp b/examples/UGM_chain.cpp
index b029379f2..58e4c14dc 100644
--- a/examples/UGM_chain.cpp
+++ b/examples/UGM_chain.cpp
@@ -79,7 +79,7 @@ int main(int argc, char** argv) {
 
 
   cout << "\nComputing Node Marginals ..(Sequential Elimination)" << endl;
-  tic_(1, "Sequential");
+  tic_(Sequential);
   for (vector<DiscreteKey>::iterator itr = nodes.begin(); itr != nodes.end();
       ++itr) {
     //Compute the marginal
@@ -89,14 +89,14 @@ int main(int argc, char** argv) {
     cout << "Node#" << setw(4) << itr->first << " :  ";
     print(margProbs);
   }
-  toc_(1, "Sequential");
+  toc_(Sequential);
 
   // Here we'll make use of DiscreteMarginals class, which makes use of
   // bayes-tree based shortcut evaluation of marginals
   DiscreteMarginals marginals(graph);
 
   cout << "\nComputing Node Marginals ..(BayesTree based)" << endl;
-  tic_(2, "Multifrontal");
+  tic_(Multifrontal);
   for (vector<DiscreteKey>::iterator itr = nodes.begin(); itr != nodes.end();
       ++itr) {
     //Compute the marginal
@@ -106,7 +106,7 @@ int main(int argc, char** argv) {
     cout << "Node#" << setw(4) << itr->first << " :  ";
     print(margProbs);
   }
-  toc_(2, "Multifrontal");
+  toc_(Multifrontal);
 
   tictoc_print_();
   return 0;
diff --git a/gtsam/base/tests/timeVirtual2.cpp b/gtsam/base/tests/timeVirtual2.cpp
index 56190b91e..c36ed9979 100644
--- a/gtsam/base/tests/timeVirtual2.cpp
+++ b/gtsam/base/tests/timeVirtual2.cpp
@@ -82,51 +82,55 @@ int main(int argc, char *argv[]) {
 
   int n = 10000000;
 
+  {
   VirtualBase** b = new VirtualBase*[n];
-  tic_(0, "Virtual");
-  tic_(0, "new");
+  tic_(Virtual);
+  tic_(new);
   for(int i=0; i<n; ++i)
     b[i] = new VirtualDerived();
-  toc_(0, "new");
-  tic_(1, "method");
+  toc_(new);
+  tic_(method);
   for(int i=0; i<n; ++i)
     b[i]->method();
-  toc_(1, "method");
-  tic_(2, "dynamic_cast");
+  toc_(method);
+  tic_(dynamic_cast);
   for(int i=0; i<n; ++i) {
     VirtualDerived* d = dynamic_cast<VirtualDerived*>(b[i]);
     if(d)
       d->method();
   }
-  toc_(2, "dynamic_cast");
-  tic_(3, "delete");
+  toc_(dynamic_cast);
+  tic_(delete);
   for(int i=0; i<n; ++i)
     delete b[i];
-  toc_(3, "delete");
-  toc_(0, "Virtual");
+  toc_(delete);
+  toc_(Virtual);
   delete[] b;
+  }
 
 
+  {
   NonVirtualDerived** d = new NonVirtualDerived*[n];
-  tic_(1, "NonVirtual");
-  tic_(0, "new");
+  tic_(NonVirtual);
+  tic_(new);
   for(int i=0; i<n; ++i)
     d[i] = new NonVirtualDerived();
-  toc_(0, "new");
-  tic_(1, "method");
+  toc_(new);
+  tic_(method);
   for(int i=0; i<n; ++i)
     d[i]->method();
-  toc_(1, "method");
-  tic_(2, "dynamic_cast (does nothing)");
+  toc_(method);
+  tic_(dynamic_cast (does nothing));
   for(int i=0; i<n; ++i)
     d[i]->method();
-  toc_(2, "dynamic_cast (does nothing)");
-  tic_(3, "delete");
+  toc_(dynamic_cast (does nothing));
+  tic_(delete);
   for(int i=0; i<n; ++i)
     delete d[i];
-  toc_(3, "delete");
-  toc_(1, "NonVirtual");
+  toc_(delete);
+  toc_(NonVirtual);
   delete[] d;
+  }
 
   tictoc_finishedIteration_();
   tictoc_print_();
diff --git a/gtsam_unstable/discrete/examples/schedulingExample.cpp b/gtsam_unstable/discrete/examples/schedulingExample.cpp
index 61fc42692..4ca18dab1 100644
--- a/gtsam_unstable/discrete/examples/schedulingExample.cpp
+++ b/gtsam_unstable/discrete/examples/schedulingExample.cpp
@@ -151,9 +151,9 @@ void solveStaged(size_t addMutex = 2) {
     scheduler.buildGraph(addMutex);
 
     // Do EXACT INFERENCE
-    tic_(3,"eliminate");
+    tic_(eliminate);
     DiscreteBayesNet::shared_ptr chordal = scheduler.eliminate();
-    toc_(3,"eliminate");
+    toc_(eliminate);
 
     // find root node
     DiscreteConditional::shared_ptr root = *(chordal->rbegin());
diff --git a/gtsam_unstable/discrete/examples/schedulingQuals12.cpp b/gtsam_unstable/discrete/examples/schedulingQuals12.cpp
index 7007bb665..af62e04a0 100644
--- a/gtsam_unstable/discrete/examples/schedulingQuals12.cpp
+++ b/gtsam_unstable/discrete/examples/schedulingQuals12.cpp
@@ -178,9 +178,9 @@ void solveStaged(size_t addMutex = 2) {
     scheduler.buildGraph(addMutex);
 
     // Do EXACT INFERENCE
-    tic_(3,"eliminate");
+    tic_(eliminate);
     DiscreteBayesNet::shared_ptr chordal = scheduler.eliminate();
-    toc_(3,"eliminate");
+    toc_(eliminate);
 
     // find root node
     DiscreteConditional::shared_ptr root = *(chordal->rbegin());
diff --git a/tests/timeIncremental.cpp b/tests/timeIncremental.cpp
index 1c2beb8bc..f1a3c5e0f 100644
--- a/tests/timeIncremental.cpp
+++ b/tests/timeIncremental.cpp
@@ -46,11 +46,11 @@ int main(int argc, char *argv[]) {
 
   cout << "Loading data..." << endl;
 
-  tic_(1, "Find datafile (script only)");
+  tic_(Find_datafile);
   string datasetFile = findExampleDataFile("w10000-odom");
   std::pair<NonlinearFactorGraph::shared_ptr, Values::shared_ptr> data =
     load2D(datasetFile);
-  toc_(1, "Find datafile (script only)");
+  toc_(Find_datafile);
 
   NonlinearFactorGraph measurements = *data.first;
   Values initial = *data.second;
@@ -66,7 +66,7 @@ int main(int argc, char *argv[]) {
     NonlinearFactorGraph newFactors;
 
     // Collect measurements and new variables for the current step
-    tic_(2, "Collect measurements (script only)");
+    tic_(Collect_measurements);
     if(step == 1) {
       //      cout << "Initializing " << 0 << endl;
       newVariables.insert(0, Pose());
@@ -114,19 +114,19 @@ int main(int argc, char *argv[]) {
       }
       ++ nextMeasurement;
     }
-    toc_(2, "Collect measurements (script only)");
+    toc_(Collect_measurements);
 
     // Update iSAM2
-    tic_(3, "Update ISAM2");
+    tic_(Update_ISAM2);
     isam2.update(newFactors, newVariables);
-    toc_(3, "Update ISAM2");
+    toc_(Update_ISAM2);
 
     if(step % 100 == 0) {
-      tic_(4, "chi2 (script only)");
+      tic_(chi2);
       Values estimate(isam2.calculateEstimate());
       double chi2 = chi2_red(isam2.getFactorsUnsafe(), estimate);
       cout << "chi2 = " << chi2 << endl;
-      toc_(4, "chi2 (script only)");
+      toc_(chi2);
     }
 
     tictoc_finishedIteration_();
@@ -141,9 +141,9 @@ int main(int argc, char *argv[]) {
   Marginals marginals(isam2.getFactorsUnsafe(), isam2.calculateEstimate());
   int i=0;
   BOOST_FOREACH(Key key, initial.keys()) {
-    tic_(5, "marginalInformation");
+    tic_(marginalInformation);
     Matrix info = marginals.marginalInformation(key);
-    toc_(5, "marginalInformation");
+    toc_(marginalInformation);
     tictoc_finishedIteration_();
     if(i % 1000 == 0)
       tictoc_print_();