diff --git a/gtsam/linear/GaussianConditional.cpp b/gtsam/linear/GaussianConditional.cpp
index eefb6302f..60187d129 100644
--- a/gtsam/linear/GaussianConditional.cpp
+++ b/gtsam/linear/GaussianConditional.cpp
@@ -12,11 +12,13 @@
 /**
  * @file   GaussianConditional.cpp
  * @brief  Conditional Gaussian Base class
- * @author Christian Potthast
+ * @author Christian Potthast, Frank Dellaert
  */
 
-#include <string.h>
-#include <functional>
+#include <gtsam/linear/linearExceptions.h>
+#include <gtsam/linear/GaussianConditional.h>
+#include <gtsam/linear/VectorValues.h>
+
 #include <boost/format.hpp>
 #ifdef __GNUC__
 #pragma GCC diagnostic push
@@ -28,9 +30,9 @@
 #pragma GCC diagnostic pop
 #endif
 
-#include <gtsam/linear/linearExceptions.h>
-#include <gtsam/linear/GaussianConditional.h>
-#include <gtsam/linear/VectorValues.h>
+#include <functional>
+#include <list>
+#include <string>
 
 using namespace std;
 
@@ -54,38 +56,36 @@ namespace gtsam {
   BaseFactor(key, R, name1, S, name2, T, d, sigmas), BaseConditional(1) {}
 
   /* ************************************************************************* */
-  void GaussianConditional::print(const string &s, const KeyFormatter& formatter) const
-  {
+  void GaussianConditional::print(const string &s, const KeyFormatter& formatter) const {
     cout << s << "  Conditional density ";
-    for(const_iterator it = beginFrontals(); it != endFrontals(); ++it) {
+    for (const_iterator it = beginFrontals(); it != endFrontals(); ++it) {
       cout << (boost::format("[%1%]")%(formatter(*it))).str() << " ";
     }
     cout << endl;
     cout << formatMatrixIndented("  R = ", get_R()) << endl;
-    for(const_iterator it = beginParents() ; it != endParents() ; ++it ) {
+    for (const_iterator it = beginParents() ; it != endParents() ; ++it) {
       cout << formatMatrixIndented((boost::format("  S[%1%] = ")%(formatter(*it))).str(), getA(it))
         << endl;
     }
     cout << formatMatrixIndented("  d = ", getb(), true) << "\n";
-    if(model_)
+    if (model_)
       model_->print("  Noise model: ");
     else
       cout << "  No noise model" << endl;
   }
 
   /* ************************************************************************* */
-  bool GaussianConditional::equals(const GaussianFactor& f, double tol) const
-  {
-    if (const GaussianConditional* c = dynamic_cast<const GaussianConditional*>(&f))
-    {
+  bool GaussianConditional::equals(const GaussianFactor& f, double tol) const {
+    if (const GaussianConditional* c = dynamic_cast<const GaussianConditional*>(&f)) {
       // check if the size of the parents_ map is the same
       if (parents().size() != c->parents().size())
         return false;
 
       // check if R_ and d_ are linear independent
       for (DenseIndex i = 0; i < Ab_.rows(); i++) {
-        list<Vector> rows1; rows1.push_back(Vector(get_R().row(i)));
-        list<Vector> rows2; rows2.push_back(Vector(c->get_R().row(i)));
+        list<Vector> rows1, rows2;
+        rows1.push_back(Vector(get_R().row(i)));
+        rows2.push_back(Vector(c->get_R().row(i)));
 
         // check if the matrices are the same
         // iterate over the parents_ map
@@ -109,16 +109,13 @@ namespace gtsam {
         return false;
 
       return true;
-    }
-    else
-    {
+    } else {
       return false;
     }
   }
 
   /* ************************************************************************* */
-  VectorValues GaussianConditional::solve(const VectorValues& x) const
-  {
+  VectorValues GaussianConditional::solve(const VectorValues& x) const {
     // Concatenate all vector values that correspond to parent variables
     const Vector xS = x.vector(FastVector<Key>(beginParents(), endParents()));
 
@@ -146,8 +143,7 @@ namespace gtsam {
 
   /* ************************************************************************* */
   VectorValues GaussianConditional::solveOtherRHS(
-    const VectorValues& parents, const VectorValues& rhs) const
-  {
+    const VectorValues& parents, const VectorValues& rhs) const {
     // Concatenate all vector values that correspond to parent variables
     Vector xS = parents.vector(FastVector<Key>(beginParents(), endParents()));
 
@@ -159,13 +155,13 @@ namespace gtsam {
     Vector soln = get_R().triangularView<Eigen::Upper>().solve(xS);
 
     // Scale by sigmas
-    if(model_)
+    if (model_)
       soln.array() *= model_->sigmas().array();
 
     // Insert solution into a VectorValues
     VectorValues result;
     DenseIndex vectorPosition = 0;
-    for(const_iterator frontal = beginFrontals(); frontal != endFrontals(); ++frontal) {
+    for (const_iterator frontal = beginFrontals(); frontal != endFrontals(); ++frontal) {
       result.insert(*frontal, soln.segment(vectorPosition, getDim(frontal)));
       vectorPosition += getDim(frontal);
     }
@@ -174,8 +170,7 @@ namespace gtsam {
   }
 
   /* ************************************************************************* */
-  void GaussianConditional::solveTransposeInPlace(VectorValues& gy) const
-  {
+  void GaussianConditional::solveTransposeInPlace(VectorValues& gy) const {
     Vector frontalVec = gy.vector(FastVector<Key>(beginFrontals(), endFrontals()));
     frontalVec = gtsam::backSubstituteUpper(frontalVec, Matrix(get_R()));
 
@@ -186,25 +181,24 @@ namespace gtsam {
       gy[*it] += -1.0 * Matrix(getA(it)).transpose() * frontalVec;
 
     // Scale by sigmas
-    if(model_)
+    if (model_)
       frontalVec.array() *= model_->sigmas().array();
 
     // Write frontal solution into a VectorValues
     DenseIndex vectorPosition = 0;
-    for(const_iterator frontal = beginFrontals(); frontal != endFrontals(); ++frontal) {
+    for (const_iterator frontal = beginFrontals(); frontal != endFrontals(); ++frontal) {
       gy[*frontal] = frontalVec.segment(vectorPosition, getDim(frontal));
       vectorPosition += getDim(frontal);
     }
   }
 
   /* ************************************************************************* */
-  void GaussianConditional::scaleFrontalsBySigma(VectorValues& gy) const
-  {
+  void GaussianConditional::scaleFrontalsBySigma(VectorValues& gy) const {
     DenseIndex vectorPosition = 0;
-    for(const_iterator frontal = beginFrontals(); frontal != endFrontals(); ++frontal) {
+    for (const_iterator frontal = beginFrontals(); frontal != endFrontals(); ++frontal) {
       gy[*frontal].array() *= model_->sigmas().segment(vectorPosition, getDim(frontal)).array();
       vectorPosition += getDim(frontal);
     }
   }
 
-}
+}  // namespace gtsam