diff --git a/gtsam/base/SymmetricBlockMatrix.cpp b/gtsam/base/SymmetricBlockMatrix.cpp
index 5eaa2df1c..7f41da137 100644
--- a/gtsam/base/SymmetricBlockMatrix.cpp
+++ b/gtsam/base/SymmetricBlockMatrix.cpp
@@ -65,8 +65,9 @@ Matrix SymmetricBlockMatrix::block(DenseIndex I, DenseIndex J) const {
 void SymmetricBlockMatrix::choleskyPartial(DenseIndex nFrontals) {
   gttic(VerticalBlockMatrix_choleskyPartial);
   DenseIndex topleft = variableColOffsets_[blockStart_];
-  if (!gtsam::choleskyPartial(matrix_, offset(nFrontals) - topleft, topleft))
+  if (!gtsam::choleskyPartial(matrix_, offset(nFrontals) - topleft, topleft)) {
     throw CholeskyFailed();
+  }
 }
 
 /* ************************************************************************* */
diff --git a/gtsam/inference/EliminationTree-inst.h b/gtsam/inference/EliminationTree-inst.h
index 333f898b8..33ba6e18d 100644
--- a/gtsam/inference/EliminationTree-inst.h
+++ b/gtsam/inference/EliminationTree-inst.h
@@ -49,8 +49,7 @@ namespace gtsam {
 
     // Do dense elimination step
     KeyVector keyAsVector(1); keyAsVector[0] = key;
-    std::pair<boost::shared_ptr<ConditionalType>, boost::shared_ptr<FactorType> > eliminationResult =
-      function(gatheredFactors, Ordering(keyAsVector));
+    auto eliminationResult = function(gatheredFactors, Ordering(keyAsVector));
 
     // Add conditional to BayesNet
     output->push_back(eliminationResult.first);
@@ -190,13 +189,13 @@ namespace gtsam {
   {
     gttic(EliminationTree_eliminate);
     // Allocate result
-    boost::shared_ptr<BayesNetType> result = boost::make_shared<BayesNetType>();
+    auto result = boost::make_shared<BayesNetType>();
 
     // Run tree elimination algorithm
     FastVector<sharedFactor> remainingFactors = inference::EliminateTree(result, *this, function);
 
     // Add remaining factors that were not involved with eliminated variables
-    boost::shared_ptr<FactorGraphType> allRemainingFactors = boost::make_shared<FactorGraphType>();
+    auto allRemainingFactors = boost::make_shared<FactorGraphType>();
     allRemainingFactors->push_back(remainingFactors_.begin(), remainingFactors_.end());
     allRemainingFactors->push_back(remainingFactors.begin(), remainingFactors.end());