diff --git a/Eigen/src/Core/MapBase.h b/Eigen/src/Core/MapBase.h
index 0151cc67f..51e041db6 100644
--- a/Eigen/src/Core/MapBase.h
+++ b/Eigen/src/Core/MapBase.h
@@ -66,11 +66,11 @@ template<typename Derived> class MapBase
     inline const Scalar* data() const { return m_data; }
 
     template<bool IsForceAligned,typename Dummy> struct force_aligned_impl {
-      AlignedDerivedType static run(MapBase& a) { return a.derived(); }
+      static AlignedDerivedType run(MapBase& a) { return a.derived(); }
     };
 
     template<typename Dummy> struct force_aligned_impl<false,Dummy> {
-      AlignedDerivedType static run(MapBase& a) { return a.derived()._convertToForceAligned(); }
+      static AlignedDerivedType run(MapBase& a) { return a.derived()._convertToForceAligned(); }
     };
 
     /** \returns an expression equivalent to \c *this but having the \c PacketAccess constant
diff --git a/Eigen/src/Core/StableNorm.h b/Eigen/src/Core/StableNorm.h
index 22809633d..6056cafab 100644
--- a/Eigen/src/Core/StableNorm.h
+++ b/Eigen/src/Core/StableNorm.h
@@ -115,20 +115,20 @@ MatrixBase<Derived>::blueNorm() const
       ei_assert(false && "the algorithm cannot be guaranteed on this computer");
     }
     iexp  = -((1-iemin)/2);
-    b1    = std::pow(double(ibeta),iexp);  // lower boundary of midrange
+    b1    = Scalar(std::pow(double(ibeta),iexp));  // lower boundary of midrange
     iexp  = (iemax + 1 - it)/2;
-    b2    = std::pow(double(ibeta),iexp);   // upper boundary of midrange
+    b2    = Scalar(std::pow(double(ibeta),iexp));   // upper boundary of midrange
 
     iexp  = (2-iemin)/2;
-    s1m   = std::pow(double(ibeta),iexp);   // scaling factor for lower range
+    s1m   = Scalar(std::pow(double(ibeta),iexp));   // scaling factor for lower range
     iexp  = - ((iemax+it)/2);
-    s2m   = std::pow(double(ibeta),iexp);   // scaling factor for upper range
+    s2m   = Scalar(std::pow(double(ibeta),iexp));   // scaling factor for upper range
 
     overfl  = rbig*s2m;             // overfow boundary for abig
-    eps     = std::pow(double(ibeta), 1-it);
+    eps     = Scalar(std::pow(double(ibeta), 1-it));
     relerr  = ei_sqrt(eps);         // tolerance for neglecting asml
     abig    = 1.0/eps - 1.0;
-    if (RealScalar(nbig)>abig)  nmax = abig;  // largest safe n
+    if (RealScalar(nbig)>abig)  nmax = int(abig);  // largest safe n
     else                        nmax = nbig;
   }
   int n = size();
diff --git a/Eigen/src/Core/TriangularMatrix.h b/Eigen/src/Core/TriangularMatrix.h
index c262ea7a7..b0362f20c 100644
--- a/Eigen/src/Core/TriangularMatrix.h
+++ b/Eigen/src/Core/TriangularMatrix.h
@@ -234,14 +234,14 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
     inline TriangularView<NestByValue<typename MatrixType::AdjointReturnType>,TransposeMode> adjoint()
     { return m_matrix.adjoint().nestByValue(); }
     /** \sa MatrixBase::adjoint() const */
-    const inline TriangularView<NestByValue<typename MatrixType::AdjointReturnType>,TransposeMode> adjoint() const
+    inline const TriangularView<NestByValue<typename MatrixType::AdjointReturnType>,TransposeMode> adjoint() const
     { return m_matrix.adjoint().nestByValue(); }
 
     /** \sa MatrixBase::transpose() */
     inline TriangularView<NestByValue<Transpose<MatrixType> >,TransposeMode> transpose()
     { return m_matrix.transpose().nestByValue(); }
     /** \sa MatrixBase::transpose() const */
-    const inline TriangularView<NestByValue<Transpose<MatrixType> >,TransposeMode> transpose() const
+    inline const TriangularView<NestByValue<Transpose<MatrixType> >,TransposeMode> transpose() const
     { return m_matrix.transpose().nestByValue(); }
 
     PlainMatrixType toDense() const
diff --git a/test/product_trsm.cpp b/test/product_trsm.cpp
index 4f0fd15be..9f372df91 100644
--- a/test/product_trsm.cpp
+++ b/test/product_trsm.cpp
@@ -25,9 +25,9 @@
 #include "main.h"
 
 #define VERIFY_TRSM(TRI,XB) { \
-    XB.setRandom(); ref = XB; \
-    TRI.template solveInPlace(XB); \
-    VERIFY_IS_APPROX(TRI.toDense() * XB, ref); \
+    (XB).setRandom(); ref = (XB); \
+    (TRI).solveInPlace(XB); \
+    VERIFY_IS_APPROX((TRI).toDense() * (XB), ref); \
   }
 
 template<typename Scalar> void trsm(int size,int cols)