diff --git a/doc/sphinx/source/examples/Hyperbolic/1D/Burgers1D.md b/doc/sphinx/source/examples/Hyperbolic/1D/Burgers1D.md
index 181a656f..574f826a 100644
--- a/doc/sphinx/source/examples/Hyperbolic/1D/Burgers1D.md
+++ b/doc/sphinx/source/examples/Hyperbolic/1D/Burgers1D.md
@@ -18,4 +18,4 @@ The wave is allowed to propagate across the domain while the area under the curv
 
 This example is implemented in:
 - [MATLAB/ OCTAVE](https://github.com/csrc-sdsu/mole/blob/main/examples/matlab_octave/burgers1D.m)
-- [C++](https://github.com/csrc-sdsu/mole/blob/main/examples/cpp/Burgers1D.cpp) 
+- [C++](https://github.com/csrc-sdsu/mole/blob/main/examples/cpp/burgers1D.cpp) 
diff --git a/examples/cpp/Burgers1D.cpp b/examples/cpp/burgers1D.cpp
similarity index 96%
rename from examples/cpp/Burgers1D.cpp
rename to examples/cpp/burgers1D.cpp
index cb8b77d9..f0007793 100644
--- a/examples/cpp/Burgers1D.cpp
+++ b/examples/cpp/burgers1D.cpp
@@ -1,92 +1,92 @@
-
-/**
- * Solving the 1D Advection Equation using a Mimetic Finite Difference Scheme
- *
- * Equation: ∂U/∂t + ∂(U²)/∂x = 0  (Nonlinear Burgers' Equation in conservative form)
- * Domain:   x ∈ [-15, 15] with m = 300 grid cells
- * Time:     Simulated until t = 10.0 with time step dt = dx (CFL condition)
- * Initial Condition: U(x,0) = exp(-x² / 50)
- * Boundary Conditions: Mimetic divergence and interpolation operators applied (implicit treatment)
- *
- * Solution is computed using a staggered grid approach, explicit time-stepping, 
- * and mimetic finite difference operators for divergence and interpolation.
- */  
-#include <armadillo>
-#include <cmath>
-#include <cstdlib>    // for EXIT_SUCCESS / EXIT_FAILURE
-#include <fstream>
-#include <iostream>
-#include <string>
-#include <iomanip>
-#include "mole.h"
-#include "utils.h"
-
-int main() {
-    constexpr double west = -15.0;
-    constexpr double east = 15.0;
-    constexpr int k = 2;
-    constexpr int m = 300;
-    constexpr double t = 10.0;
-
-    const double dx = (east - west) / m;
-    const double dt = dx;
-
-    Divergence D(k, m, dx);
-    Interpol I(m, 1.0);
-
-    // Spatial grid (including ghost cells)
-    arma::vec xgrid(m + 2);
-    xgrid(0) = west;
-    xgrid(m + 1) = east;
-    for (int i = 1; i <= m; ++i) {
-        xgrid(i) = west + (i - 0.5) * dx;
-    }
-
-    // Initial condition
-    arma::vec U = arma::exp(-arma::square(xgrid) / 50.0);
-
-    // Sanity check: matrix dimensions
-    if (D.n_cols != I.n_rows || I.n_cols != U.n_rows) {
-        std::cerr << "Error: Incompatible matrix dimensions!" << std::endl;
-        return EXIT_FAILURE;
-    }
-
-    int total_steps = static_cast<int>(t / dt);
-    int plot_interval = total_steps / 5;
-
-    for (int step = 0; step <= total_steps; ++step) {
-        double time = step * dt;
-
-        // Explicit update
-        U += (-dt / 2.0) * (D * (I * arma::square(U)));
-
-        if (step % plot_interval == 0) {
-            double area = Utils::trapz(xgrid, U);
-            std::cout << "Time step: " << step
-                      << ", Time: " << time
-                      << ", Trapz Area: " << area
-                      << ", U_min: " << U.min()
-                      << ", U_max: " << U.max()
-                      << ", U_center: " << U(U.n_elem / 2)
-                      << std::endl;
-
-            std::string filename = "output_step_" + std::to_string(step) + ".dat";
-            std::ofstream outfile(filename);
-            if (!outfile) {
-                std::cerr << "Error: Could not open file for writing: " << filename << std::endl;
-                return EXIT_FAILURE;
-            }
-
-            outfile << "# x    U(x)\n";
-            for (arma::uword i = 0; i < xgrid.n_elem; ++i) {
-                outfile << std::setw(12) << xgrid(i) << " "
-                        << std::setw(12) << U(i) << "\n";
-            }
-        }
-    }
-
-    return EXIT_SUCCESS;
-}
-
-
-
+
+/**
+ * Solving the 1D Advection Equation using a Mimetic Finite Difference Scheme
+ *
+ * Equation: ∂U/∂t + ∂(U²)/∂x = 0  (Nonlinear Burgers' Equation in conservative form)
+ * Domain:   x ∈ [-15, 15] with m = 300 grid cells
+ * Time:     Simulated until t = 10.0 with time step dt = dx (CFL condition)
+ * Initial Condition: U(x,0) = exp(-x² / 50)
+ * Boundary Conditions: Mimetic divergence and interpolation operators applied (implicit treatment)
+ *
+ * Solution is computed using a staggered grid approach, explicit time-stepping, 
+ * and mimetic finite difference operators for divergence and interpolation.
+ */  
+#include <armadillo>
+#include <cmath>
+#include <cstdlib>    // for EXIT_SUCCESS / EXIT_FAILURE
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <iomanip>
+#include "mole.h"
+#include "utils.h"
+
+int main() {
+    constexpr double west = -15.0;
+    constexpr double east = 15.0;
+    constexpr int k = 2;
+    constexpr int m = 300;
+    constexpr double t = 10.0;
+
+    const double dx = (east - west) / m;
+    const double dt = dx;
+
+    Divergence D(k, m, dx);
+    Interpol I(m, 1.0);
+
+    // Spatial grid (including ghost cells)
+    arma::vec xgrid(m + 2);
+    xgrid(0) = west;
+    xgrid(m + 1) = east;
+    for (int i = 1; i <= m; ++i) {
+        xgrid(i) = west + (i - 0.5) * dx;
+    }
+
+    // Initial condition
+    arma::vec U = arma::exp(-arma::square(xgrid) / 50.0);
+
+    // Sanity check: matrix dimensions
+    if (D.n_cols != I.n_rows || I.n_cols != U.n_rows) {
+        std::cerr << "Error: Incompatible matrix dimensions!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    int total_steps = static_cast<int>(t / dt);
+    int plot_interval = total_steps / 5;
+
+    for (int step = 0; step <= total_steps; ++step) {
+        double time = step * dt;
+
+        // Explicit update
+        U += (-dt / 2.0) * (D * (I * arma::square(U)));
+
+        if (step % plot_interval == 0) {
+            double area = Utils::trapz(xgrid, U);
+            std::cout << "Time step: " << step
+                      << ", Time: " << time
+                      << ", Trapz Area: " << area
+                      << ", U_min: " << U.min()
+                      << ", U_max: " << U.max()
+                      << ", U_center: " << U(U.n_elem / 2)
+                      << std::endl;
+
+            std::string filename = "output_step_" + std::to_string(step) + ".dat";
+            std::ofstream outfile(filename);
+            if (!outfile) {
+                std::cerr << "Error: Could not open file for writing: " << filename << std::endl;
+                return EXIT_FAILURE;
+            }
+
+            outfile << "# x    U(x)\n";
+            for (arma::uword i = 0; i < xgrid.n_elem; ++i) {
+                outfile << std::setw(12) << xgrid(i) << " "
+                        << std::setw(12) << U(i) << "\n";
+            }
+        }
+    }
+
+    return EXIT_SUCCESS;
+}
+
+
+
diff --git a/examples/cpp/Poisson2D.cpp b/examples/cpp/poisson2D.cpp
similarity index 97%
rename from examples/cpp/Poisson2D.cpp
rename to examples/cpp/poisson2D.cpp
index 6945b0cd..60d669c9 100644
--- a/examples/cpp/Poisson2D.cpp
+++ b/examples/cpp/poisson2D.cpp
@@ -1,67 +1,67 @@
-/**
- * Solving the 2D Poisson Equation with Robin Boundary Conditions
- * 
- * Equation: ∇²u = f(x, y)  (Poisson Equation)
- * Domain:   Defined on a (m+2) x (n+2) grid with spacing dx, dy
- * Boundary Conditions:
- *   - Bottom boundary (y = 0) has a Dirichlet condition: u = 100
- *   - Other boundaries are subject to Robin conditions as defined in RobinBC
- *
- * Solution is computed using a Mimetic Finite Difference Laplacian and solved via Armadillo's sparse solver.
- */
-
-#include <armadillo>
-#include "mole.h"
-#include <iomanip>
-#include <iostream>
-#include <cmath> // For std::abs
-
-using namespace arma;
-
-int main() {
-    constexpr uint16_t k = 2;  // Order of accuracy
-    constexpr uint32_t m = 5;  // Vertical resolution
-    constexpr uint32_t n = 6;  // Horizontal resolution
-    constexpr double dx = 1.0, dy = 1.0; // Grid spacing
-
-    // Construct the 2D Mimetic Laplacian
-    Laplacian L(k, m, n, dx, dy);
-    RobinBC BC(k, m, dx, n, dy, 1.0, 0.0);
-    L = L + BC;
-
-    // Define RHS matrix and apply boundary conditions
-    mat RHS = zeros(m + 2, n + 2);
-    RHS.row(0).fill(100.0); // Known value at the bottom boundary
-
-    // Convert RHS to a column vector
-    vec rhs = vectorise(RHS);
-
-    // Solve the system
-    vec SOL = spsolve(L, rhs);
-
-    // Reshape solution back to 2D form
-    mat SOL2D = reshape(SOL, m + 2, n + 2);
-
-    // Display solution without negative zeros or excessive decimal places
-    std::cout << "2D Poisson Solution:\n";
-    for (uint32_t i = 0; i < SOL2D.n_rows; ++i) {
-        for (uint32_t j = 0; j < SOL2D.n_cols; ++j) {
-            double value = SOL2D(i, j);
-            if (std::abs(value) < 1e-10) {  // If value is very close to zero, set it to exactly 0.0
-                value = 0.0;
-            }
-
-            // Adjust precision and remove unnecessary decimal places
-            if (std::abs(value - std::round(value)) < 1e-4) {  // If value is close to an integer
-                std::cout << std::fixed << std::setprecision(0) << value;  // No decimals
-            } else {
-                std::cout << std::fixed << std::setprecision(4) << value;  // Four decimal places
-            }
-
-            std::cout << "\t";  // Tab separation
-        }
-        std::cout << "\n";
-    }
-
-    return 0;
-}
+/**
+ * Solving the 2D Poisson Equation with Robin Boundary Conditions
+ * 
+ * Equation: ∇²u = f(x, y)  (Poisson Equation)
+ * Domain:   Defined on a (m+2) x (n+2) grid with spacing dx, dy
+ * Boundary Conditions:
+ *   - Bottom boundary (y = 0) has a Dirichlet condition: u = 100
+ *   - Other boundaries are subject to Robin conditions as defined in RobinBC
+ *
+ * Solution is computed using a Mimetic Finite Difference Laplacian and solved via Armadillo's sparse solver.
+ */
+
+#include <armadillo>
+#include "mole.h"
+#include <iomanip>
+#include <iostream>
+#include <cmath> // For std::abs
+
+using namespace arma;
+
+int main() {
+    constexpr uint16_t k = 2;  // Order of accuracy
+    constexpr uint32_t m = 5;  // Vertical resolution
+    constexpr uint32_t n = 6;  // Horizontal resolution
+    constexpr double dx = 1.0, dy = 1.0; // Grid spacing
+
+    // Construct the 2D Mimetic Laplacian
+    Laplacian L(k, m, n, dx, dy);
+    RobinBC BC(k, m, dx, n, dy, 1.0, 0.0);
+    L = L + BC;
+
+    // Define RHS matrix and apply boundary conditions
+    mat RHS = zeros(m + 2, n + 2);
+    RHS.row(0).fill(100.0); // Known value at the bottom boundary
+
+    // Convert RHS to a column vector
+    vec rhs = vectorise(RHS);
+
+    // Solve the system
+    vec SOL = spsolve(L, rhs);
+
+    // Reshape solution back to 2D form
+    mat SOL2D = reshape(SOL, m + 2, n + 2);
+
+    // Display solution without negative zeros or excessive decimal places
+    std::cout << "2D Poisson Solution:\n";
+    for (uint32_t i = 0; i < SOL2D.n_rows; ++i) {
+        for (uint32_t j = 0; j < SOL2D.n_cols; ++j) {
+            double value = SOL2D(i, j);
+            if (std::abs(value) < 1e-10) {  // If value is very close to zero, set it to exactly 0.0
+                value = 0.0;
+            }
+
+            // Adjust precision and remove unnecessary decimal places
+            if (std::abs(value - std::round(value)) < 1e-4) {  // If value is close to an integer
+                std::cout << std::fixed << std::setprecision(0) << value;  // No decimals
+            } else {
+                std::cout << std::fixed << std::setprecision(4) << value;  // Four decimal places
+            }
+
+            std::cout << "\t";  // Tab separation
+        }
+        std::cout << "\n";
+    }
+
+    return 0;
+}
diff --git a/examples/cpp/Schrodinger2D.cpp b/examples/cpp/schrodinger2D.cpp
similarity index 100%
rename from examples/cpp/Schrodinger2D.cpp
rename to examples/cpp/schrodinger2D.cpp