From b886ae336246941b2621d7d4c2397383f5e9fbec Mon Sep 17 00:00:00 2001
From: "Klamkin, Michael" <mklamkin3@gatech.edu>
Date: Thu, 12 Feb 2026 12:50:13 -0500
Subject: [PATCH 1/2] fix parametric obj

---
 src/NonLinearProgram/nlp_utilities.jl |  8 ++++---
 test/nlp_program.jl                   | 32 +++++++++++++++++++++++++++
 2 files changed, 37 insertions(+), 3 deletions(-)

diff --git a/src/NonLinearProgram/nlp_utilities.jl b/src/NonLinearProgram/nlp_utilities.jl
index edcbe6e8..8f3a79b1 100644
--- a/src/NonLinearProgram/nlp_utilities.jl
+++ b/src/NonLinearProgram/nlp_utilities.jl
@@ -489,9 +489,11 @@ function _compute_sensitivity(model::Model; tol = 1e-6)
     # Dual bounds upper
     ∂s[((num_w+num_cons+num_lower+1):end), :] *= -_sense_multiplier
 
-    # dual wrt parameter
+    grad = _compute_gradient(model)
     primal_idx = [i.value for i in model.cache.primal_vars]
-    df_dx = _compute_gradient(model)[primal_idx]
-    df_dp = df_dx'∂s[1:num_vars, :]
+    params_idx = [i.value for i in model.cache.params]
+    df_dx = grad[primal_idx]
+    df_dp_direct = grad[params_idx]
+    df_dp = df_dx'∂s[1:num_vars, :] + df_dp_direct'
     return ∂s, df_dp
 end
diff --git a/test/nlp_program.jl b/test/nlp_program.jl
index c266c715..e47819a8 100644
--- a/test/nlp_program.jl
+++ b/test/nlp_program.jl
@@ -740,6 +740,38 @@ function test_ObjectiveSensitivity_model2()
     @test isapprox(dp, -1.5; atol = 1e-4)
 end
 
+function test_ObjectiveSensitivity_direct_param_contrib()
+    model = DiffOpt.nonlinear_diff_model(Ipopt.Optimizer)
+    set_silent(model)
+
+    p_val = 3.0
+    @variable(model, p ∈ MOI.Parameter(p_val))
+    @variable(model, x ≥ 1)
+    @objective(model, Min, p^2 * x^2)
+
+    optimize!(model)
+    @assert is_solved_and_feasible(model)
+
+    Δp = 0.1
+    DiffOpt.set_forward_parameter(model, p, Δp)
+    DiffOpt.forward_differentiate!(model)
+
+    df_dp = MOI.get(model, DiffOpt.ForwardObjectiveSensitivity())
+    @test isapprox(df_dp, 2 * p_val * Δp, atol=1e-8)   # ≈ 0.6 for p=3
+
+    ε = 1e-6
+    df_dp_fd = (begin
+        set_parameter_value(p, p_val + ε)
+        optimize!(model)
+        Δp * objective_value(model)
+    end - begin
+        set_parameter_value(p, p_val - ε)
+        optimize!(model)
+        Δp * objective_value(model)
+    end) / (2ε)
+    
+    @test isapprox(df_dp, df_dp_fd, atol=1e-4)
+end
 function test_ObjectiveSensitivity_subset_parameters()
     # Model with 10 parameters, differentiate only w.r.t. 3rd and 7th
     model = Model(() -> DiffOpt.diff_optimizer(Ipopt.Optimizer))

From e72beedaabaa9e2c2aca8bd358dbf8d3bb64e503 Mon Sep 17 00:00:00 2001
From: "Klamkin, Michael" <mklamkin3@gatech.edu>
Date: Thu, 12 Feb 2026 13:03:39 -0500
Subject: [PATCH 2/2] format

---
 test/nlp_program.jl | 27 +++++++++++++++------------
 1 file changed, 15 insertions(+), 12 deletions(-)

diff --git a/test/nlp_program.jl b/test/nlp_program.jl
index e47819a8..34a41b8d 100644
--- a/test/nlp_program.jl
+++ b/test/nlp_program.jl
@@ -757,20 +757,23 @@ function test_ObjectiveSensitivity_direct_param_contrib()
     DiffOpt.forward_differentiate!(model)
 
     df_dp = MOI.get(model, DiffOpt.ForwardObjectiveSensitivity())
-    @test isapprox(df_dp, 2 * p_val * Δp, atol=1e-8)   # ≈ 0.6 for p=3
+    @test isapprox(df_dp, 2 * p_val * Δp, atol = 1e-8)   # ≈ 0.6 for p=3
 
     ε = 1e-6
-    df_dp_fd = (begin
-        set_parameter_value(p, p_val + ε)
-        optimize!(model)
-        Δp * objective_value(model)
-    end - begin
-        set_parameter_value(p, p_val - ε)
-        optimize!(model)
-        Δp * objective_value(model)
-    end) / (2ε)
-    
-    @test isapprox(df_dp, df_dp_fd, atol=1e-4)
+    df_dp_fd =
+        (
+            begin
+                set_parameter_value(p, p_val + ε)
+                optimize!(model)
+                Δp * objective_value(model)
+            end - begin
+                set_parameter_value(p, p_val - ε)
+                optimize!(model)
+                Δp * objective_value(model)
+            end
+        ) / (2ε)
+
+    @test isapprox(df_dp, df_dp_fd, atol = 1e-4)
 end
 function test_ObjectiveSensitivity_subset_parameters()
     # Model with 10 parameters, differentiate only w.r.t. 3rd and 7th