diff --git a/src/Optimization/CMakeLists.txt b/src/Optimization/CMakeLists.txt
index 22fc3226..30e35d54 100644
--- a/src/Optimization/CMakeLists.txt
+++ b/src/Optimization/CMakeLists.txt
@@ -8,7 +8,7 @@ set(hiopOptimization_SRC
   hiopKKTLinSys.cpp
   KktLinSysLowRank.cpp
   hiopKKTLinSysMDS.cpp 
-  hiopHessianLowRank.cpp 
+  HessianDiagPlusRowRank.cpp 
   hiopDualsUpdater.cpp 
   hiopNlpTransforms.cpp
   hiopPDPerturbation.cpp
@@ -28,7 +28,7 @@ set(hiopOptimization_INTERFACE_HEADERS
   hiopDualsUpdater.hpp
   hiopFactAcceptor.hpp
   hiopFilter.hpp
-  hiopHessianLowRank.hpp
+  HessianDiagPlusRowRank.hpp
   hiopIterate.hpp
   hiopKKTLinSys.hpp
   hiopKKTLinSysDense.hpp
diff --git a/src/Optimization/hiopHessianLowRank.cpp b/src/Optimization/HessianDiagPlusRowRank.cpp
similarity index 84%
rename from src/Optimization/hiopHessianLowRank.cpp
rename to src/Optimization/HessianDiagPlusRowRank.cpp
index e76bfe5a..70257811 100644
--- a/src/Optimization/hiopHessianLowRank.cpp
+++ b/src/Optimization/HessianDiagPlusRowRank.cpp
@@ -46,7 +46,7 @@
 // Lawrence Livermore National Security, LLC, and shall not be used for advertising or 
 // product endorsement purposes.
 
-#include "hiopHessianLowRank.hpp"
+#include "HessianDiagPlusRowRank.hpp"
 #include "LinAlgFactory.hpp"
 #include "hiopVectorPar.hpp"
 
@@ -75,7 +75,7 @@ using namespace std;
 namespace hiop
 {
 
-hiopHessianLowRank::hiopHessianLowRank(hiopNlpDenseConstraints* nlp_in, int max_mem_len)
+HessianDiagPlusRowRank::HessianDiagPlusRowRank(hiopNlpDenseConstraints* nlp_in, int max_mem_len)
   : l_max_(max_mem_len),
     l_curr_(-1),
     sigma_(1.),
@@ -165,7 +165,7 @@ hiopHessianLowRank::hiopHessianLowRank(hiopNlpDenseConstraints* nlp_in, int max_
 
 }  
 
-hiopHessianLowRank::~hiopHessianLowRank()
+HessianDiagPlusRowRank::~HessianDiagPlusRowRank()
 {
   delete DhInv_;
   delete Dx_;
@@ -215,7 +215,7 @@ hiopHessianLowRank::~hiopHessianLowRank()
   }
 }
 
-void hiopHessianLowRank::alloc_for_limited_mem(const size_type& mem_length)
+void HessianDiagPlusRowRank::alloc_for_limited_mem(const size_type& mem_length)
 {
   //note: St_ and Yt_ always have l_curr_ rows
   if(l_curr_ == mem_length) {
@@ -234,7 +234,7 @@ void hiopHessianLowRank::alloc_for_limited_mem(const size_type& mem_length)
   D_  = LinearAlgebraFactory::create_vector("DEFAULT", mem_length);
 }
 
-bool hiopHessianLowRank::update_logbar_diag(const hiopVector& Dx)
+bool HessianDiagPlusRowRank::update_logbar_diag(const hiopVector& Dx)
 {
   DhInv_->setToConstant(sigma_);
   DhInv_->axpy(1.0,Dx);
@@ -243,13 +243,13 @@ bool hiopHessianLowRank::update_logbar_diag(const hiopVector& Dx)
   assert(DhInv_->allPositive());
 #endif
   DhInv_->invert();
-  nlp_->log->write("hiopHessianLowRank: inverse diag DhInv:", *DhInv_, hovMatrices);
+  nlp_->log->write("HessianDiagPlusRowRank: inverse diag DhInv:", *DhInv_, hovMatrices);
   matrix_changed_ = true;
   return true;
 }
 
 #ifdef HIOP_DEEPCHECKS
-void hiopHessianLowRank::print(FILE* f, hiopOutVerbosity v, const char* msg) const
+void HessianDiagPlusRowRank::print(FILE* f, hiopOutVerbosity v, const char* msg) const
 {
   fprintf(f, "%s\n", msg);
 #ifdef HIOP_DEEPCHECKS
@@ -266,7 +266,9 @@ void hiopHessianLowRank::print(FILE* f, hiopOutVerbosity v, const char* msg) con
 #ifdef HIOP_DEEPCHECKS
   nlp_->log->write("V", *Vmat_, v);
 #else
-  fprintf(f, "V matrix is available at this point (only its LAPACK factorization). Print it in updateInternalBFGSRepresentation() instead, before factorizeV()\n");
+  fprintf(f,
+          "V matrix is available at this point (only its LAPACK factorization). Print it in "
+          "updateInternalBFGSRepresentation() instead, before factorizeV()\n");
 #endif
   nlp_->log->write("L", *L_, v);
   nlp_->log->write("D", *D_, v);
@@ -275,13 +277,15 @@ void hiopHessianLowRank::print(FILE* f, hiopOutVerbosity v, const char* msg) con
 
 #include <limits>
 
-bool hiopHessianLowRank::update(const hiopIterate& it_curr, const hiopVector& grad_f_curr_,
-				const hiopMatrix& Jac_c_curr_, const hiopMatrix& Jac_d_curr_)
+bool HessianDiagPlusRowRank::update(const hiopIterate& it_curr,
+                                    const hiopVector& grad_f_curr,
+                                    const hiopMatrix& Jac_c_curr_in,
+                                    const hiopMatrix& Jac_d_curr_in)
 {
   nlp_->runStats.tmSolverInternal.start();
 
-  const hiopMatrixDense& Jac_c_curr = dynamic_cast<const hiopMatrixDense&>(Jac_c_curr_);
-  const hiopMatrixDense& Jac_d_curr = dynamic_cast<const hiopMatrixDense&>(Jac_d_curr_);
+  const hiopMatrixDense& Jac_c_curr = dynamic_cast<const hiopMatrixDense&>(Jac_c_curr_in);
+  const hiopMatrixDense& Jac_d_curr = dynamic_cast<const hiopMatrixDense&>(Jac_d_curr_in);
 
 #ifdef HIOP_DEEPCHECKS
   assert(it_curr.zl->matchesPattern(nlp_->get_ixl()));
@@ -291,7 +295,7 @@ bool hiopHessianLowRank::update(const hiopIterate& it_curr, const hiopVector& gr
 #endif
   //on first call l_curr_=-1
   if(l_curr_>=0) {
-    size_type n=grad_f_curr_.get_size();
+    size_type n = grad_f_curr.get_size();
     //compute s_new = x_curr-x_prev
     hiopVector& s_new = new_n_vec1(n);
     s_new.copyFrom(*it_curr.x);
@@ -302,7 +306,7 @@ bool hiopHessianLowRank::update(const hiopIterate& it_curr, const hiopVector& gr
       //compute y_new = \grad J(x_curr,\lambda_curr) - \grad J(x_prev, \lambda_curr) (yes, J(x_prev, \lambda_curr))
       //              = graf_f_curr-grad_f_prev + (Jac_c_curr-Jac_c_prev)yc_curr+ (Jac_d_curr-Jac_c_prev)yd_curr - zl_curr*s_new + zu_curr*s_new
       hiopVector& y_new = new_n_vec2(n);
-      y_new.copyFrom(grad_f_curr_); 
+      y_new.copyFrom(grad_f_curr); 
       y_new.axpy(-1., *grad_f_prev_);
       Jac_c_curr.transTimesVec  (1.0, y_new, 1.0, *it_curr.yc);
       //!opt if nlp_->Jac_c_isLinear no need for the multiplications
@@ -314,9 +318,13 @@ bool hiopHessianLowRank::update(const hiopIterate& it_curr, const hiopVector& gr
       double sTy = s_new.dotProductWith(y_new), s_nrm2=s_new.twonorm(), y_nrm2=y_new.twonorm();
 
 #ifdef HIOP_DEEPCHECKS
-      nlp_->log->printf(hovLinAlgScalarsVerb, "hiopHessianLowRank: s^T*y=%20.14e ||s||=%20.14e ||y||=%20.14e\n", sTy, s_nrm2, y_nrm2);
-      nlp_->log->write("hiopHessianLowRank s_new",s_new, hovIteration);
-      nlp_->log->write("hiopHessianLowRank y_new",y_new, hovIteration);
+      nlp_->log->printf(hovLinAlgScalarsVerb,
+                        "HessianDiagPlusRowRank: s^T*y=%20.14e ||s||=%20.14e ||y||=%20.14e\n",
+                        sTy,
+                        s_nrm2,
+                        y_nrm2);
+      nlp_->log->write("HessianDiagPlusRowRank s_new",s_new, hovIteration);
+      nlp_->log->write("HessianDiagPlusRowRank y_new",y_new, hovIteration);
 #endif
       if(sTy>s_nrm2*y_nrm2*sqrt(std::numeric_limits<double>::epsilon())) { //sTy far away from zero
 
@@ -344,7 +352,7 @@ bool hiopHessianLowRank::update(const hiopIterate& it_curr, const hiopVector& gr
           }
         } //end of l_max_>0
 #ifdef HIOP_DEEPCHECKS
-        nlp_->log->printf(hovMatrices, "\nhiopHessianLowRank: these are L and D from the BFGS compact representation\n");
+        nlp_->log->printf(hovMatrices, "\nHessianDiagPlusRowRank: these are L and D from the BFGS compact representation\n");
         nlp_->log->write("L", *L_, hovMatrices);
         nlp_->log->write("D", *D_, hovMatrices);
         nlp_->log->printf(hovMatrices, "\n");
@@ -372,27 +380,27 @@ bool hiopHessianLowRank::update(const hiopIterate& it_curr, const hiopVector& gr
         } // else of the switch
         //safe guard it
         sigma_ = fmax(fmin(sigma_safe_max_, sigma_), sigma_safe_min_);
-        nlp_->log->printf(hovLinAlgScalars, "hiopHessianLowRank: sigma was updated to %22.16e\n", sigma_);
+        nlp_->log->printf(hovLinAlgScalars, "HessianDiagPlusRowRank: sigma was updated to %22.16e\n", sigma_);
       } else { //sTy is too small or negative -> skip
         nlp_->log->printf(hovLinAlgScalars,
-                          "hiopHessianLowRank: s^T*y=%12.6e not positive enough... skipping the Hessian update\n",
+                          "HessianDiagPlusRowRank: s^T*y=%12.6e not positive enough... skipping the Hessian update\n",
                           sTy);
       }
     } else {// norm of s_new is too small -> skip
       nlp_->log->printf(hovLinAlgScalars,
-                        "hiopHessianLowRank: ||s_new||=%12.6e too small... skipping the Hessian update\n",
+                        "HessianDiagPlusRowRank: ||s_new||=%12.6e too small... skipping the Hessian update\n",
                         s_infnorm);
     }
     //save this stuff for next update
     it_prev_->copyFrom(it_curr);
-    grad_f_prev_->copyFrom(grad_f_curr_);
+    grad_f_prev_->copyFrom(grad_f_curr);
     Jac_c_prev_->copyFrom(Jac_c_curr);
     Jac_d_prev_->copyFrom(Jac_d_curr);
-    nlp_->log->printf(hovLinAlgScalarsVerb, "hiopHessianLowRank: storing the iteration info as 'previous'\n", s_infnorm);
+    nlp_->log->printf(hovLinAlgScalarsVerb, "HessianDiagPlusRowRank: storing the iteration info as 'previous'\n", s_infnorm);
   } else {
     //this is the first optimization iterate, just save the iterate and exit
     it_prev_->copyFrom(it_curr);
-    grad_f_prev_->copyFrom(grad_f_curr_);
+    grad_f_prev_->copyFrom(grad_f_curr);
     Jac_c_prev_->copyFrom(Jac_c_curr);
     Jac_d_prev_->copyFrom(Jac_d_curr);
 
@@ -414,7 +422,7 @@ bool hiopHessianLowRank::update(const hiopIterate& it_curr, const hiopVector& gr
  * In this function V is factorized and it will hold the factors at the end of the function
  * Note that L, D, S, and Y are from the BFGS secant representation and are updated/computed in 'update'
  */
-void hiopHessianLowRank::updateInternalBFGSRepresentation()
+void HessianDiagPlusRowRank::updateInternalBFGSRepresentation()
 {
   size_type n=St_->n();
   size_type l=St_->m();
@@ -511,7 +519,7 @@ void hiopHessianLowRank::updateInternalBFGSRepresentation()
  * M is is nxn, S,Y are nxl, V is upper triangular 2lx2l, and x is nx1
  * Remember we store Yt=Y^T and St=S^T
  */  
-void hiopHessianLowRank::solve(const hiopVector& rhsx, hiopVector& x)
+void HessianDiagPlusRowRank::solve(const hiopVector& rhsx, hiopVector& x)
 {
   if(matrix_changed_) {
     updateInternalBFGSRepresentation();
@@ -569,10 +577,10 @@ void hiopHessianLowRank::solve(const hiopVector& rhsx, hiopVector& x)
  * W is kxk, S,Y are nxl, DhInv,B0 are n, V is 2lx2l
  * X is kxn
  */ 
-void hiopHessianLowRank::sym_mat_times_inverse_times_mattrans(double beta,
-                                                              hiopMatrixDense& W, 
-                                                              double alpha,
-                                                              const hiopMatrixDense& X)
+void HessianDiagPlusRowRank::sym_mat_times_inverse_times_mattrans(double beta,
+                                                                  hiopMatrixDense& W, 
+                                                                  double alpha,
+                                                                  const hiopMatrixDense& X)
 {
   if(matrix_changed_) {
     updateInternalBFGSRepresentation();
@@ -653,7 +661,7 @@ void hiopHessianLowRank::sym_mat_times_inverse_times_mattrans(double beta,
 #endif 
 }
 
-void hiopHessianLowRank::factorizeV()
+void HessianDiagPlusRowRank::factorizeV()
 {
   int N = V_->n();
   int lda = N;
@@ -695,10 +703,10 @@ void hiopHessianLowRank::factorizeV()
   DSYTRF(&uplo, &N, V_->local_data(), &lda, V_ipiv_vec_, V_work_vec_->local_data(), &lwork, &info);
   
   if(info<0) {
-    nlp_->log->printf(hovError, "hiopHessianLowRank::factorizeV error: %d arg to dsytrf has an illegal value\n", -info);
+    nlp_->log->printf(hovError, "HessianDiagPlusRowRank::factorizeV error: %d arg to dsytrf has an illegal value\n", -info);
   } else if(info>0) {
     nlp_->log->printf(hovError,
-                     "hiopHessianLowRank::factorizeV error: %d entry in the factorization's diagonal is exactly zero. "
+                     "HessianDiagPlusRowRank::factorizeV error: %d entry in the factorization's diagonal is exactly zero. "
                      "Division by zero will occur if a solve is attempted.\n",
                      info);
   }
@@ -709,7 +717,7 @@ void hiopHessianLowRank::factorizeV()
 
 }
 
-void hiopHessianLowRank::solveWithV(hiopVector& rhs_s, hiopVector& rhs_y)
+void HessianDiagPlusRowRank::solveWithV(hiopVector& rhs_s, hiopVector& rhs_y)
 {
   int N = V_->n();
   if(N==0) {
@@ -719,8 +727,8 @@ void hiopHessianLowRank::solveWithV(hiopVector& rhs_s, hiopVector& rhs_y)
   int l = rhs_s.get_size();
 
 #ifdef HIOP_DEEPCHECKS
-  nlp_->log->write("hiopHessianLowRank::solveWithV: RHS IN 's' part: ", rhs_s, hovMatrices);
-  nlp_->log->write("hiopHessianLowRank::solveWithV: RHS IN 'y' part: ", rhs_y, hovMatrices);
+  nlp_->log->write("HessianDiagPlusRowRank::solveWithV: RHS IN 's' part: ", rhs_s, hovMatrices);
+  nlp_->log->write("HessianDiagPlusRowRank::solveWithV: RHS IN 'y' part: ", rhs_y, hovMatrices);
   hiopVector* rhs_saved= LinearAlgebraFactory::create_vector("DEFAULT", rhs_s.get_size()+rhs_y.get_size());
   rhs_saved->copyFromStarting(0, rhs_s);
   rhs_saved->copyFromStarting(l, rhs_y);
@@ -738,7 +746,7 @@ void hiopHessianLowRank::solveWithV(hiopVector& rhs_s, hiopVector& rhs_y)
   DSYTRS(&uplo, &N, &one, V_->local_data(), &lda, V_ipiv_vec_, rhs.local_data(), &N, &info);
 
   if(info<0) {
-    nlp_->log->printf(hovError, "hiopHessianLowRank::solveWithV error: %d arg to dsytrf has an illegal value\n", -info);
+    nlp_->log->printf(hovError, "HessianDiagPlusRowRank::solveWithV error: %d arg to dsytrf has an illegal value\n", -info);
   }
   assert(info==0);
 
@@ -754,17 +762,17 @@ void hiopHessianLowRank::solveWithV(hiopVector& rhs_s, hiopVector& rhs_y)
   double nrmrhs=rhs_saved->infnorm();
   Vmat_->timesVec(1.0, *rhs_saved, -1.0, rhs);
   double nrmres=rhs_saved->infnorm();
-  //nlp_->log->printf(hovLinAlgScalars, "hiopHessianLowRank::solveWithV 1rhs: rel resid norm=%g\n", nrmres/(1+nrmrhs));
-  nlp_->log->printf(hovScalars, "hiopHessianLowRank::solveWithV 1rhs: rel resid norm=%g\n", nrmres/(1+nrmrhs));
+  //nlp_->log->printf(hovLinAlgScalars, "HessianDiagPlusRowRank::solveWithV 1rhs: rel resid norm=%g\n", nrmres/(1+nrmrhs));
+  nlp_->log->printf(hovScalars, "HessianDiagPlusRowRank::solveWithV 1rhs: rel resid norm=%g\n", nrmres/(1+nrmrhs));
   if(nrmres>1e-8) {
-    nlp_->log->printf(hovWarning, "hiopHessianLowRank::solveWithV large residual=%g\n", nrmres);
+    nlp_->log->printf(hovWarning, "HessianDiagPlusRowRank::solveWithV large residual=%g\n", nrmres);
   }
   delete rhs_saved;
 #endif
 
 }
 
-void hiopHessianLowRank::solveWithV(hiopMatrixDense& rhs)
+void HessianDiagPlusRowRank::solveWithV(hiopMatrixDense& rhs)
 {
   int N = V_->n();
   if(0==N) {
@@ -786,7 +794,7 @@ void hiopHessianLowRank::solveWithV(hiopMatrixDense& rhs)
   DSYTRS(&uplo, &N, &nrhs, V_->local_data(), &lda, V_ipiv_vec_, rhs.local_data(), &ldb, &info);
 
   if(info<0) {
-    nlp_->log->printf(hovError, "hiopHessianLowRank::solveWithV error: %d arg to dsytrf has an illegal value\n", -info);
+    nlp_->log->printf(hovError, "HessianDiagPlusRowRank::solveWithV error: %d arg to dsytrf has an illegal value\n", -info);
   }
   assert(info==0);
 #ifdef HIOP_DEEPCHECKS
@@ -806,7 +814,7 @@ void hiopHessianLowRank::solveWithV(hiopMatrixDense& rhs)
     double nrmres = r->infnorm();
     if(nrmres>1e-8) {
       nlp_->log->printf(hovWarning,
-                        "hiopHessianLowRank::solveWithV mult-rhs: rhs number %d has large resid norm=%g\n",
+                        "HessianDiagPlusRowRank::solveWithV mult-rhs: rhs number %d has large resid norm=%g\n",
                         k,
                         nrmres);
     }
@@ -814,7 +822,7 @@ void hiopHessianLowRank::solveWithV(hiopMatrixDense& rhs)
       resnorm=nrmres/(nrmrhs+1);
     }
   }
-  nlp_->log->printf(hovLinAlgScalars, "hiopHessianLowRank::solveWithV mult-rhs: rel resid norm=%g\n", resnorm);
+  nlp_->log->printf(hovLinAlgScalars, "HessianDiagPlusRowRank::solveWithV mult-rhs: rel resid norm=%g\n", resnorm);
   delete x;
   delete r;
   delete rhs_saved;
@@ -822,7 +830,7 @@ void hiopHessianLowRank::solveWithV(hiopMatrixDense& rhs)
 
 }
 
-void hiopHessianLowRank::growL(const int& lmem_curr, const int& lmem_max, const hiopVector& YTs)
+void HessianDiagPlusRowRank::growL(const int& lmem_curr, const int& lmem_max, const hiopVector& YTs)
 {
   int l = L_->m();
 #ifdef HIOP_DEEPCHECKS
@@ -855,7 +863,7 @@ void hiopHessianLowRank::growL(const int& lmem_curr, const int& lmem_max, const
   L_ = newL;
 }
 
-void hiopHessianLowRank::growD(const int& lmem_curr, const int& lmem_max, const double& sTy)
+void HessianDiagPlusRowRank::growD(const int& lmem_curr, const int& lmem_max, const double& sTy)
 {
   int l = D_->get_size();
   assert(l==lmem_curr);
@@ -873,7 +881,7 @@ void hiopHessianLowRank::growD(const int& lmem_curr, const int& lmem_max, const
 /* L_{ij} = s_{i-1}^T y_{j-1}, if i>j, otherwise zero. Here i,j = 0,1,...,l_curr-1
  * L_new = lift and shift L to the left; replace last row with [Yts;0]
  */
-void hiopHessianLowRank::updateL(const hiopVector& YTs, const double& sTy)
+void HessianDiagPlusRowRank::updateL(const hiopVector& YTs, const double& sTy)
 {
   int l=YTs.get_size();
   assert(l==L_->m());
@@ -907,7 +915,7 @@ void hiopHessianLowRank::updateL(const hiopVector& YTs, const double& sTy)
   //L_mat[lm1][lm1]=0.0;
   L_mat[lm1*l+lm1] = 0.0;
 }
-void hiopHessianLowRank::updateD(const double& sTy)
+void HessianDiagPlusRowRank::updateD(const double& sTy)
 {
   int l=D_->get_size();
   double* D_vec = D_->local_data();
@@ -917,7 +925,7 @@ void hiopHessianLowRank::updateD(const double& sTy)
   D_vec[l-1] = sTy;
 }
 
-hiopVector&  hiopHessianLowRank::new_l_vec1(int l)
+hiopVector&  HessianDiagPlusRowRank::new_l_vec1(int l)
 {
   if(l_vec1_!=nullptr && l_vec1_->get_size()==l) {
     return *l_vec1_;
@@ -929,7 +937,7 @@ hiopVector&  hiopHessianLowRank::new_l_vec1(int l)
   return *l_vec1_;
 }
 
-hiopVector&  hiopHessianLowRank::new_l_vec2(int l)
+hiopVector&  HessianDiagPlusRowRank::new_l_vec2(int l)
 {
   if(l_vec2_!=nullptr && l_vec2_->get_size()==l) {
     return *l_vec2_;
@@ -941,7 +949,7 @@ hiopVector&  hiopHessianLowRank::new_l_vec2(int l)
   return *l_vec2_;
 }
 
-hiopMatrixDense& hiopHessianLowRank::new_lxl_mat1(int l)
+hiopMatrixDense& HessianDiagPlusRowRank::new_lxl_mat1(int l)
 {
   if(lxl_mat1_!=nullptr) {
     if(l==lxl_mat1_->m()) {
@@ -955,7 +963,7 @@ hiopMatrixDense& hiopHessianLowRank::new_lxl_mat1(int l)
   return *lxl_mat1_;
 }
 
-hiopMatrixDense& hiopHessianLowRank::new_kx2l_mat1(int k, int l)
+hiopMatrixDense& HessianDiagPlusRowRank::new_kx2l_mat1(int k, int l)
 {
   const int twol=2*l;
   if(nullptr!=kx2l_mat1_) {
@@ -971,7 +979,7 @@ hiopMatrixDense& hiopHessianLowRank::new_kx2l_mat1(int k, int l)
   return *kx2l_mat1_;
 }
 
-hiopMatrixDense& hiopHessianLowRank::new_kxl_mat1(int k, int l)
+hiopMatrixDense& HessianDiagPlusRowRank::new_kxl_mat1(int k, int l)
 {
   if(kxl_mat1_!=nullptr) {
     assert(kxl_mat1_->m()==k);
@@ -986,7 +994,7 @@ hiopMatrixDense& hiopHessianLowRank::new_kxl_mat1(int k, int l)
   return *kxl_mat1_;
 }
 
-hiopMatrixDense& hiopHessianLowRank::new_S1(const hiopMatrixDense& X, const hiopMatrixDense& St)
+hiopMatrixDense& HessianDiagPlusRowRank::new_S1(const hiopMatrixDense& X, const hiopMatrixDense& St)
 {
   //S1 is X*some_diag*S  (kxl). Here St=S^T is lxn and X is kxn (l BFGS memory size, k number of constraints)
   size_type k = X.m();
@@ -1007,7 +1015,7 @@ hiopMatrixDense& hiopHessianLowRank::new_S1(const hiopMatrixDense& X, const hiop
   return *S1_;
 }
 
-hiopMatrixDense& hiopHessianLowRank::new_Y1(const hiopMatrixDense& X, const hiopMatrixDense& Yt)
+hiopMatrixDense& HessianDiagPlusRowRank::new_Y1(const hiopMatrixDense& X, const hiopMatrixDense& Yt)
 {
   //Y1 is X*somediag*Y (kxl). Here Yt=Y^T is lxn,  X is kxn
   size_type k = X.m();
@@ -1029,7 +1037,7 @@ hiopMatrixDense& hiopHessianLowRank::new_Y1(const hiopMatrixDense& X, const hiop
 }
 #ifdef HIOP_DEEPCHECKS
 
-void hiopHessianLowRank::times_vec_no_logbar_term(double beta, hiopVector& y, double alpha, const hiopVector&x)
+void HessianDiagPlusRowRank::times_vec_no_logbar_term(double beta, hiopVector& y, double alpha, const hiopVector&x)
 {
   this->times_vec_common(beta, y, alpha, x, false);
 }
@@ -1037,7 +1045,7 @@ void hiopHessianLowRank::times_vec_no_logbar_term(double beta, hiopVector& y, do
 #endif //HIOP_DEEPCHECKS
 
 
-void hiopHessianLowRank::
+void HessianDiagPlusRowRank::
 times_vec_common(double beta, hiopVector& y, double alpha, const hiopVector& x, bool addLogTerm) const
 {
   size_type n=St_->n();
@@ -1050,7 +1058,7 @@ times_vec_common(double beta, hiopVector& y, double alpha, const hiopVector& x,
 
   bool print=false;
   if(print) {
-    nlp_->log->printf(hovMatrices, "---hiopHessianLowRank::times_vec \n");
+    nlp_->log->printf(hovMatrices, "---HessianDiagPlusRowRank::times_vec \n");
     nlp_->log->write("S=", *St_, hovMatrices);
     nlp_->log->write("Y=", *Yt_, hovMatrices);
     nlp_->log->write("DhInv=", *DhInv_, hovMatrices);
@@ -1076,7 +1084,7 @@ times_vec_common(double beta, hiopVector& y, double alpha, const hiopVector& x,
     
     if(skTyk < std::numeric_limits<double>::epsilon()) {
       nlp_->log->printf(hovLinAlgScalars,
-                        "hiopHessianLowRank: ||s_k^T*y_k||=%12.6e too small and was set it to mach eps = %12.6e \n",
+                        "HessianDiagPlusRowRank: ||s_k^T*y_k||=%12.6e too small and was set it to mach eps = %12.6e \n",
                         skTyk,
                         std::numeric_limits<double>::epsilon());
       skTyk = std::numeric_limits<double>::epsilon();
@@ -1127,12 +1135,12 @@ times_vec_common(double beta, hiopVector& y, double alpha, const hiopVector& x,
 
 }
 
-void hiopHessianLowRank::times_vec(double beta, hiopVector& y, double alpha, const hiopVector&x)
+void HessianDiagPlusRowRank::times_vec(double beta, hiopVector& y, double alpha, const hiopVector&x)
 {
   this->times_vec_common(beta, y, alpha, x);
 }
 
-void hiopHessianLowRank::timesVec(double beta, hiopVector& y, double alpha, const hiopVector&x) const
+void HessianDiagPlusRowRank::timesVec(double beta, hiopVector& y, double alpha, const hiopVector&x) const
 {
   this->times_vec_common(beta, y, alpha, x);
 }
@@ -1145,11 +1153,11 @@ void hiopHessianLowRank::timesVec(double beta, hiopVector& y, double alpha, cons
  * W is kxk local, X is kxn distributed and Diag is n, distributed
  * The ops are perform locally. The reduce is done separately/externally to decrease comm
  */
-void hiopHessianLowRank::sym_mat_times_diag_times_mattrans_local(double beta,
-                                                                 hiopMatrixDense& W,
-                                                                 double alpha,
-                                                                 const hiopMatrixDense& X,
-                                                                 const hiopVector& d)
+void HessianDiagPlusRowRank::sym_mat_times_diag_times_mattrans_local(double beta,
+                                                                     hiopMatrixDense& W,
+                                                                     double alpha,
+                                                                     const hiopMatrixDense& X,
+                                                                     const hiopVector& d)
 {
   size_type k=W.m();
   size_type n_local=X.get_local_size_n();
@@ -1186,10 +1194,10 @@ void hiopHessianLowRank::sym_mat_times_diag_times_mattrans_local(double beta,
 }
 
 /* W=S*D*X^T, where S is lxn, D is diag nxn, and X is kxn */
-void hiopHessianLowRank::mat_times_diag_times_mattrans_local(hiopMatrixDense& W,
-                                                             const hiopMatrixDense& S,
-                                                             const hiopVector& d,
-                                                             const hiopMatrixDense& X)
+void HessianDiagPlusRowRank::mat_times_diag_times_mattrans_local(hiopMatrixDense& W,
+                                                                 const hiopMatrixDense& S,
+                                                                 const hiopVector& d,
+                                                                 const hiopMatrixDense& X)
 {
 #ifdef HIOP_DEEPCHECKS
   assert(S.n()==d.get_size());
diff --git a/src/Optimization/hiopHessianLowRank.hpp b/src/Optimization/HessianDiagPlusRowRank.hpp
similarity index 98%
rename from src/Optimization/hiopHessianLowRank.hpp
rename to src/Optimization/HessianDiagPlusRowRank.hpp
index 759db8b5..963bde48 100644
--- a/src/Optimization/hiopHessianLowRank.hpp
+++ b/src/Optimization/HessianDiagPlusRowRank.hpp
@@ -88,11 +88,11 @@ namespace hiop
  * Parallel computations: Dk, B0 are distributed vectors, M is distributed 
  * column-wise, and N is local (stored on all processors).
  */
-class hiopHessianLowRank : public hiopMatrix
+class HessianDiagPlusRowRank : public hiopMatrix
 {
 public:
-  hiopHessianLowRank(hiopNlpDenseConstraints* nlp_in, int max_memory_length);
-  virtual ~hiopHessianLowRank();
+  HessianDiagPlusRowRank(hiopNlpDenseConstraints* nlp_in, int max_memory_length);
+  virtual ~HessianDiagPlusRowRank();
 
   /// Updates Hessian if hereditary positive definitness is maintained and returns true, otherwise false.
   virtual bool update(const hiopIterate& x_curr,
@@ -282,9 +282,9 @@ class hiopHessianLowRank : public hiopMatrix
   void solveWithV(hiopVector& rhs_s, hiopVector& rhs_y);
   void solveWithV(hiopMatrixDense& rhs);
 private:
-  hiopHessianLowRank() {};
-  hiopHessianLowRank(const hiopHessianLowRank&) {};
-  hiopHessianLowRank& operator=(const hiopHessianLowRank&) {return *this;};
+  HessianDiagPlusRowRank() {};
+  HessianDiagPlusRowRank(const HessianDiagPlusRowRank&) {};
+  HessianDiagPlusRowRank& operator=(const HessianDiagPlusRowRank&) {return *this;};
 
   /* methods that need to be implemented as the class inherits from hiopMatrix*/
 public:
diff --git a/src/Optimization/KktLinSysLowRank.cpp b/src/Optimization/KktLinSysLowRank.cpp
index 90745cbe..11178a12 100644
--- a/src/Optimization/KktLinSysLowRank.cpp
+++ b/src/Optimization/KktLinSysLowRank.cpp
@@ -87,7 +87,7 @@ bool KktLinSysLowRank::update(const hiopIterate* iter,
                               const hiopVector* grad_f,
                               const hiopMatrixDense* Jac_c,
                               const hiopMatrixDense* Jac_d,
-                              hiopHessianLowRank* hess_low_rank)
+                              HessianDiagPlusRowRank* hess_low_rank)
 {
   nlp_->runStats.tmSolverInternal.start();
 
@@ -133,7 +133,7 @@ bool KktLinSysLowRank::update(const hiopIterate* iter,
  * and then solving for dx from
  *  dx = - (H+Dx)^{-1}*(Jc^T*dyc+Jd^T*dyd - rx)
  *
- * Note that ops H+Dx are provided by hiopHessianLowRank
+ * Note that ops H+Dx are provided by HessianDiagPlusRowRank
  */
 bool KktLinSysLowRank::solveCompressed(hiopVector& rx,
                                        hiopVector& ryc,
@@ -160,7 +160,7 @@ bool KktLinSysLowRank::solveCompressed(hiopVector& rx,
   J.copyRowsFrom(*Jac_c_de, nlp_->m_eq(), 0); //!opt
   J.copyRowsFrom(*Jac_d_de, nlp_->m_ineq(), nlp_->m_eq());//!opt
 
-  auto* hess_low_rank = dynamic_cast<hiopHessianLowRank*>(Hess_);
+  auto* hess_low_rank = dynamic_cast<HessianDiagPlusRowRank*>(Hess_);
   
   //N =  J*(Hess\J')
   //Hess->symmetricTimesMat(0.0, *N, 1.0, J);
@@ -460,7 +460,7 @@ double KktLinSysLowRank::errorCompressedLinsys(const hiopVector& rx,
                                                const hiopVector& dyd)
 {
   nlp_->log->printf(hovLinAlgScalars, "KktLinSysLowRank::errorCompressedLinsys residuals norm:\n");
-  auto* hess_low_rank = dynamic_cast<hiopHessianLowRank*>(Hess_);
+  auto* hess_low_rank = dynamic_cast<HessianDiagPlusRowRank*>(Hess_);
   
   double derr = -1.;
   double aux;
diff --git a/src/Optimization/KktLinSysLowRank.hpp b/src/Optimization/KktLinSysLowRank.hpp
index 702d6faa..525a1907 100644
--- a/src/Optimization/KktLinSysLowRank.hpp
+++ b/src/Optimization/KktLinSysLowRank.hpp
@@ -68,8 +68,8 @@ namespace hiop
  * by low-rank matrix plus a multiple of identity and the number of the constraints is not
  * too large. 
  * 
- * It works with Hessian being a HessianLowRank class and the constraints Jacobian being
- * hiopMatrixDense. 
+ * It works with Hessian being a HessianDiagPlusLowRank class and the constraints Jacobian 
+ * being hiopMatrixDense. 
  *
  * This class solves the XYcYd compression of the full KKT. See solveCompressed method 
  * for details on the approach used to solve the linear system. 
@@ -90,7 +90,7 @@ class KktLinSysLowRank : public hiopKKTLinSysCompressedXYcYd
   {
     const hiopMatrixDense* Jac_c_ = dynamic_cast<const hiopMatrixDense*>(Jac_c);
     const hiopMatrixDense* Jac_d_ = dynamic_cast<const hiopMatrixDense*>(Jac_d);
-    hiopHessianLowRank* Hess_ = dynamic_cast<hiopHessianLowRank*>(Hess);
+    HessianDiagPlusRowRank* Hess_ = dynamic_cast<HessianDiagPlusRowRank*>(Hess);
     if(Jac_c_==nullptr || Jac_d_==nullptr || Hess_==nullptr) {
       assert(false);
       return false;
@@ -103,7 +103,7 @@ class KktLinSysLowRank : public hiopKKTLinSysCompressedXYcYd
 		      const hiopVector* grad_f,
 		      const hiopMatrixDense* Jac_c,
                       const hiopMatrixDense* Jac_d,
-		      hiopHessianLowRank* Hess);
+		      HessianDiagPlusRowRank* Hess);
 
   virtual bool build_kkt_matrix(const hiopPDPerturbation& pdreg)
   {
@@ -148,7 +148,7 @@ class KktLinSysLowRank : public hiopKKTLinSysCompressedXYcYd
   /// @brief perform y=beta*y+alpha*H*x without the log barrier term from H
   void HessianTimesVec_noLogBarrierTerm(double beta, hiopVector& y, double alpha, const hiopVector& x)
   {
-    hiopHessianLowRank* hesslowrank = dynamic_cast<hiopHessianLowRank*>(Hess_);
+    HessianDiagPlusRowRank* hesslowrank = dynamic_cast<HessianDiagPlusRowRank*>(Hess_);
     assert(nullptr != hesslowrank);
     hesslowrank->times_vec_no_logbar_term(beta, y, alpha, x);
   }
diff --git a/src/Optimization/hiopAlgFilterIPM.cpp b/src/Optimization/hiopAlgFilterIPM.cpp
index d5248418..4d13f9d8 100644
--- a/src/Optimization/hiopAlgFilterIPM.cpp
+++ b/src/Optimization/hiopAlgFilterIPM.cpp
@@ -971,7 +971,7 @@ hiopSolveStatus hiopAlgFilterIPMQuasiNewton::run()
   resetSolverStatus();
 
   //types of linear algebra objects are known now
-  hiopHessianLowRank* Hess = dynamic_cast<hiopHessianLowRank*>(_Hess_Lagr);
+  auto* Hess = dynamic_cast<HessianDiagPlusRowRank*>(_Hess_Lagr);
 
   nlp->runStats.initialize();
   nlp->runStats.kkt.initialize();
@@ -1599,7 +1599,7 @@ void hiopAlgFilterIPMQuasiNewton::save_state_to_sidre_group(::axom::sidre::Group
   SidreHelper::copy_iterate_to_views(group, "alg_iterate_", *it_curr);
   
   //state of quasi-Newton Hessian approximation
-  hiopHessianLowRank& hqn = dynamic_cast<hiopHessianLowRank&>(*_Hess_Lagr);
+  HessianDiagPlusRowRank& hqn = dynamic_cast<HessianDiagPlusRowRank&>(*_Hess_Lagr);
   const double hqn_params[] = {(double)hqn.l_max_,
                                (double)hqn.l_curr_,
                                hqn.sigma_,
@@ -1712,7 +1712,7 @@ void hiopAlgFilterIPMQuasiNewton::load_state_from_sidre_group(const sidre::Group
   //
   //state of quasi-Newton Hessian approximation
   //
-  hiopHessianLowRank& hqn = dynamic_cast<hiopHessianLowRank&>(*_Hess_Lagr);
+  HessianDiagPlusRowRank& hqn = dynamic_cast<HessianDiagPlusRowRank&>(*_Hess_Lagr);
   //!!!note: nparams needs to match the # of params from save_state_to_sidre_group
   const int nhqn_params = 5;
   double hqn_params[nhqn_params];
diff --git a/src/Optimization/hiopAlgFilterIPM.hpp b/src/Optimization/hiopAlgFilterIPM.hpp
index bf90fa97..10653bbe 100644
--- a/src/Optimization/hiopAlgFilterIPM.hpp
+++ b/src/Optimization/hiopAlgFilterIPM.hpp
@@ -60,7 +60,7 @@
 #include "hiopIterate.hpp"
 #include "hiopResidual.hpp"
 #include "hiopFilter.hpp"
-#include "hiopHessianLowRank.hpp"
+#include "HessianDiagPlusRowRank.hpp"
 #include "hiopKKTLinSys.hpp"
 #include "hiopLogBarProblem.hpp"
 #include "hiopDualsUpdater.hpp"
diff --git a/src/Optimization/hiopIterate.hpp b/src/Optimization/hiopIterate.hpp
index 4039c452..ba8fc923 100644
--- a/src/Optimization/hiopIterate.hpp
+++ b/src/Optimization/hiopIterate.hpp
@@ -166,7 +166,7 @@ class hiopIterate
   friend class hiopKKTLinSysDenseXYcYd;
   friend class hiopKKTLinSysDenseXDYcYd;
   friend class KktLinSysLowRank;
-  friend class hiopHessianLowRank;
+  friend class HessianDiagPlusRowRank;
   friend class hiopKKTLinSysCompressedMDSXYcYd;
   friend class hiopHessianInvLowRank_obsolette;
   friend class hiopKKTLinSysSparse;
diff --git a/src/Optimization/hiopKKTLinSys.hpp b/src/Optimization/hiopKKTLinSys.hpp
index 817106a8..98dee25e 100644
--- a/src/Optimization/hiopKKTLinSys.hpp
+++ b/src/Optimization/hiopKKTLinSys.hpp
@@ -51,7 +51,7 @@
 
 #include "hiopIterate.hpp"
 #include "hiopResidual.hpp"
-#include "hiopHessianLowRank.hpp"
+#include "HessianDiagPlusRowRank.hpp"
 #include "hiopPDPerturbation.hpp"
 #include "hiopLinSolver.hpp"
 #include "hiopFactAcceptor.hpp"
diff --git a/src/Optimization/hiopNlpFormulation.cpp b/src/Optimization/hiopNlpFormulation.cpp
index 5204681d..7ffb404d 100644
--- a/src/Optimization/hiopNlpFormulation.cpp
+++ b/src/Optimization/hiopNlpFormulation.cpp
@@ -54,7 +54,7 @@
  */
 
 #include "hiopNlpFormulation.hpp"
-#include "hiopHessianLowRank.hpp"
+#include "HessianDiagPlusRowRank.hpp"
 #include "hiopVector.hpp"
 #include "LinAlgFactory.hpp"
 #include "hiopLogger.hpp"
@@ -1636,7 +1636,7 @@ hiopMatrixDense* hiopNlpDenseConstraints::alloc_Jac_cons()
 
 hiopMatrix* hiopNlpDenseConstraints::alloc_Hess_Lagr()
 {
-  return new hiopHessianLowRank(this, this->options->GetInteger("secant_memory_len"));
+  return new HessianDiagPlusRowRank(this, this->options->GetInteger("secant_memory_len"));
 }
 
 hiopMatrixDense* hiopNlpDenseConstraints::alloc_multivector_primal(int nrows, int maxrows/*=-1*/) const
diff --git a/src/Optimization/hiopNlpFormulation.hpp b/src/Optimization/hiopNlpFormulation.hpp
index ed522f4d..a9467ae5 100644
--- a/src/Optimization/hiopNlpFormulation.hpp
+++ b/src/Optimization/hiopNlpFormulation.hpp
@@ -461,7 +461,7 @@ class hiopNlpDenseConstraints : public hiopNlpFormulation
   virtual hiopMatrixDense* alloc_Jac_c();
   virtual hiopMatrixDense* alloc_Jac_d();
   virtual hiopMatrixDense* alloc_Jac_cons();
-  //returns hiopHessianLowRank which (fakely) inherits from hiopMatrix
+  //returns HessianDiagPlusRowRank which (fakely) inherits from hiopMatrix
   virtual hiopMatrix* alloc_Hess_Lagr();
 
   /* this is in general for a dense matrix with n_vars cols and a small number of 
diff --git a/src/Utils/hiopLogger.cpp b/src/Utils/hiopLogger.cpp
index 29d3452a..705c19e0 100644
--- a/src/Utils/hiopLogger.cpp
+++ b/src/Utils/hiopLogger.cpp
@@ -50,7 +50,7 @@
 
 #include "hiopVector.hpp"
 #include "hiopResidual.hpp"
-#include "hiopHessianLowRank.hpp"
+#include "HessianDiagPlusRowRank.hpp"
 #include "hiopFilter.hpp"
 #include "hiopOptions.hpp"
 
@@ -97,7 +97,10 @@ void hiopLogger::write(const char* msg, const hiopIterate& it, hiopOutVerbosity
 }
 
 #ifdef HIOP_DEEPCHECKS
-void hiopLogger::write(const char* msg, const hiopHessianLowRank& Hess, hiopOutVerbosity v, int loggerid/*=0*/)
+void hiopLogger::write(const char* msg,
+                       const HessianDiagPlusRowRank& Hess,
+                       hiopOutVerbosity v,
+                       int loggerid/*=0*/)
 {
   if(master_rank_ != my_rank_) return;
   hiopOutVerbosity _verb = (hiopOutVerbosity) options_->GetInteger("verbosity_level");
@@ -106,7 +109,7 @@ void hiopLogger::write(const char* msg, const hiopHessianLowRank& Hess, hiopOutV
 }
 #endif
 
-void hiopLogger::write(const char* msg, const hiopOptions& options,     hiopOutVerbosity v, int loggerid/*=0*/)
+void hiopLogger::write(const char* msg, const hiopOptions& options, hiopOutVerbosity v, int loggerid/*=0*/)
 {
   if(master_rank_ != my_rank_) return;
   hiopOutVerbosity _verb = (hiopOutVerbosity) options_->GetInteger("verbosity_level");
diff --git a/src/Utils/hiopLogger.hpp b/src/Utils/hiopLogger.hpp
index 2b211179..8bb68e52 100644
--- a/src/Utils/hiopLogger.hpp
+++ b/src/Utils/hiopLogger.hpp
@@ -62,7 +62,7 @@ class hiopVector;
 class hiopResidual;
 class hiopIterate;
 class hiopMatrix;
-class hiopHessianLowRank;
+class HessianDiagPlusRowRank;
 class hiopNlpFormulation;
 class hiopOptions;
 class hiopFilter;
@@ -105,7 +105,7 @@ class hiopLogger
   void write(const char* msg, const hiopIterate& r,           hiopOutVerbosity v, int loggerid=0);
   void write(const char* msg, const hiopMatrix& M,            hiopOutVerbosity v, int loggerid=0);
 #ifdef HIOP_DEEPCHECKS
-  void write(const char* msg, const hiopHessianLowRank& Hess, hiopOutVerbosity v, int loggerid=0);
+  void write(const char* msg, const HessianDiagPlusRowRank& Hess, hiopOutVerbosity v, int loggerid=0);
 #endif
   void write(const char* msg, const hiopNlpFormulation& nlp,  hiopOutVerbosity v, int loggerid=0);
   void write(const char* msg, const hiopOptions& options,     hiopOutVerbosity v, int loggerid=0);