diff --git a/cpp/NonlinearOptimizer-inl.h b/cpp/NonlinearOptimizer-inl.h
index ab1e4786e..e12497b8f 100644
--- a/cpp/NonlinearOptimizer-inl.h
+++ b/cpp/NonlinearOptimizer-inl.h
@@ -54,9 +54,17 @@ namespace gtsam {
 	// linearize and optimize
 	/* ************************************************************************* */
 	template<class G, class C>
-	VectorConfig NonlinearOptimizer<G, C>::delta() const {
+	VectorConfig NonlinearOptimizer<G, C>::linearizeAndOptimizeForDelta() const {
+
+		// linearize the non-linear graph around the current config
+		// which gives a linear optimization problem in the tangent space
 		LinearFactorGraph linear = graph_->linearize(*config_);
-		return linear.optimize(*ordering_);
+
+		// solve for the optimal displacement in the tangent space
+		VectorConfig delta = linear.optimize(*ordering_);
+
+		// return
+		return delta;
 	}
 
 	/* ************************************************************************* */
@@ -67,7 +75,7 @@ namespace gtsam {
 			verbosityLevel verbosity) const {
 
 		// linearize and optimize
-		VectorConfig delta = this->delta();
+		VectorConfig delta = linearizeAndOptimizeForDelta();
 
 		// maybe show output
 		if (verbosity >= DELTA)
diff --git a/cpp/NonlinearOptimizer.h b/cpp/NonlinearOptimizer.h
index 21d003645..d900b9ef7 100644
--- a/cpp/NonlinearOptimizer.h
+++ b/cpp/NonlinearOptimizer.h
@@ -20,9 +20,9 @@ namespace gtsam {
 	 * and then one of the optimization routines is called. These recursively iterate
 	 * until convergence. All methods are functional and return a new state.
 	 *
-	 * The class is parameterized by the Config class type, in order to optimize
-	 * over non-vector configurations as well.
-	 * To use in code, include <gtsam/NonlinearOptimizer.cpp> in your cpp file
+	 * The class is parameterized by the Graph type and Config class type, the latter
+	 * in order to be able to optimize over non-vector configurations as well.
+	 * To use in code, include <gtsam/NonlinearOptimizer-inl.h> in your cpp file
 	 * (the trick in http://www.ddj.com/cpp/184403420 did not work).
 	 */
 	template<class FactorGraph, class Config>
@@ -96,9 +96,9 @@ namespace gtsam {
 
 		/**
 		 *  linearize and optimize
-		 *  Thi returns an VectorConfig, i.e., vectors in tangent space of Config
+		 *  This returns an VectorConfig, i.e., vectors in tangent space of Config
 		 */
-		VectorConfig delta() const;
+		VectorConfig linearizeAndOptimizeForDelta() const;
 
 		/**
 		 * Do one Gauss-Newton iteration and return next state
diff --git a/cpp/testNonlinearOptimizer.cpp b/cpp/testNonlinearOptimizer.cpp
index 87730cada..d9024985c 100644
--- a/cpp/testNonlinearOptimizer.cpp
+++ b/cpp/testNonlinearOptimizer.cpp
@@ -47,7 +47,7 @@ TEST( NonlinearOptimizer, delta )
 	ord1.push_back("l1");
 	ord1.push_back("x1");
 	Optimizer optimizer1(fg, ord1, initial);
-	VectorConfig actual1 = optimizer1.delta();
+	VectorConfig actual1 = optimizer1.linearizeAndOptimizeForDelta();
 	CHECK(assert_equal(actual1,expected));
 
 	// Check another
@@ -56,7 +56,7 @@ TEST( NonlinearOptimizer, delta )
 	ord2.push_back("x2");
 	ord2.push_back("l1");
 	Optimizer optimizer2(fg, ord2, initial);
-	VectorConfig actual2 = optimizer2.delta();
+	VectorConfig actual2 = optimizer2.linearizeAndOptimizeForDelta();
 	CHECK(assert_equal(actual2,expected));
 
 	// And yet another...
@@ -65,7 +65,7 @@ TEST( NonlinearOptimizer, delta )
 	ord3.push_back("x1");
 	ord3.push_back("x2");
 	Optimizer optimizer3(fg, ord3, initial);
-	VectorConfig actual3 = optimizer3.delta();
+	VectorConfig actual3 = optimizer3.linearizeAndOptimizeForDelta();
 	CHECK(assert_equal(actual3,expected));
 }