diff --git a/test/knitroapi.jl b/test/knitroapi.jl
index 128a4a2..a5bf2a1 100644
--- a/test/knitroapi.jl
+++ b/test/knitroapi.jl
@@ -447,98 +447,104 @@ end
 end
 
 
-@testset "Fourth problem test" begin
-    kc = KNITRO.KN_new()
-
-    # START: Some specific parameter settings
-    KNITRO.KN_set_param(kc, "presolve", 0)
-    KNITRO.KN_set_param(kc, "outlev", 0)
-    KNITRO.KN_set_param(kc, "gradopt", 2)
-    KNITRO.KN_set_param(kc, "hessopt", 2)
-    # END:   Some specific parameter settings
-
-    function evalF_evalGA(kc, cb, evalRequest, evalResult, userParams)
-        x = evalRequest.x
-        evalRequestCode = evalRequest.evalRequestCode
-
-        if evalRequestCode == KNITRO.KN_RC_EVALFC
-            # Evaluate nonlinear objective
-            evalResult.obj[1] = x[1]^2 * x[3] + x[2]^3 * x[3]^2
-        elseif evalRequestCode == KNITRO.KN_RC_EVALGA
-            evalResult.objGrad[1] = 2 * x[1] * x[3]
-            evalResult.objGrad[2] = 3 * x[2]^2 * x[3]^2
-            evalResult.objGrad[3] = x[1]^2 + 2 * x[2]^3 * x[3]
-        else
-            return KNITRO.KN_RC_CALLBACK_ERR
-        end
-        return 0
-    end
-
-    # Define objective goal
-    objGoal = KNITRO.KN_OBJGOAL_MAXIMIZE
-    KNITRO.KN_set_obj_goal(kc, objGoal)
-
-    # Add the variables and set their bounds.
-    nV = 3
-    KNITRO.KN_add_vars(kc, nV)
-    KNITRO.KN_set_var_lobnds(kc, [0, 0.1, 0])
-    KNITRO.KN_set_var_upbnds(kc, [0., 2, 2])
-    KNITRO.KN_set_var_types(kc, [KNITRO.KN_VARTYPE_CONTINUOUS, KNITRO.KN_VARTYPE_INTEGER, KNITRO.KN_VARTYPE_INTEGER])
-
-    # Define an initial point.
-    KNITRO.KN_set_var_primal_init_values(kc, [1, 1, 1.5])
-    KNITRO.KN_set_var_dual_init_values(kc, [1., 1, 1, 1])
-
-    # Add the constraints and set their lower bounds.
-    nC = 1
-    KNITRO.KN_add_cons(kc, nC)
-    KNITRO.KN_set_con_lobnds(kc, [0.1])
-    KNITRO.KN_set_con_upbnds(kc, [2 * 2 * 0.99])
-
-    # Load quadratic structure x1*x2 for the constraint.
-    KNITRO.KN_add_con_quadratic_struct(kc, 0, 1, 2, 1.0)
-
-    # Define callback functions.
-    cb = KNITRO.KN_add_objective_callback(kc, evalF_evalGA)
-    KNITRO.KN_set_cb_grad(kc, cb, evalF_evalGA)
-
-    # Define complementarity constraints
-    KNITRO.KN_set_compcons(kc, [KNITRO.KN_CCTYPE_VARVAR], Int32[0], Int32[1])
-
-    # Set MIP parameters
-    KNITRO.KN_set_mip_branching_priorities(kc, Int32[0, 1, 2])
-    # not compatible with MPEC constraint as a variable cannot be involved in two different complementarity constraints.
-    # KNITRO.KN_set_mip_intvar_strategies(kc, 2, KNITRO.KN_MIP_INTVAR_STRATEGY_MPEC)
-    KNITRO.KN_set_mip_node_callback(kc, callback("mip_node"))
-
-    # Set var, con and obj names
-    KNITRO.KN_set_var_names(kc, ["myvar1", "myvar2", "myvar3"])
-    KNITRO.KN_set_con_names(kc, ["mycon1"])
-    KNITRO.KN_set_obj_name(kc, "myobj")
-
-    # Set feasibility tolerances
-    KNITRO.KN_set_var_feastols(kc, [0.1, 0.001, 0.1])
-    KNITRO.KN_set_con_feastols(kc, [0.1])
-    KNITRO.KN_set_compcon_feastols(kc, [0.1])
-
-    # Set finite differences step size
-    KNITRO.KN_set_cb_relstepsizes(kc, cb, [0.1, 0.001, 0.1])
-
-    # Solve the problem.
-    status = KNITRO.KN_solve(kc)
-    # Test for return codes 0 for optimality, and KN_RC_MIP_EXH_FEAS for all nodes explored, assumed optimal
-    @test status == 0 || status == KNITRO.KN_RC_MIP_EXH_FEAS
-
-    @test KNITRO.KN_get_mip_number_nodes(kc) >= 1
-    @test KNITRO.KN_get_mip_number_solves(kc) >= 1
-    @test KNITRO.KN_get_mip_relaxation_bnd(kc) ≈ 31.3632000015
-    @test KNITRO.KN_get_mip_lastnode_obj(kc) ≈ 31.3632000015
-    @test KNITRO.KN_get_con_values(kc)[1] == 4.0
-    @test KNITRO.KN_get_mip_incumbent_obj(kc) ≈ 32.0
-    @test KNITRO.KN_get_mip_incumbent_x(kc) == 0.0
-
-    KNITRO.KN_free(kc)
-end
+#=
+    Note: deactivate temporarily at the test yields
+    a segfault on Julia 1.7.
+=#
+
+# @testset "Fourth problem test" begin
+#     kc = KNITRO.KN_new()
+
+#     # START: Some specific parameter settings
+#     KNITRO.KN_set_param(kc, "presolve", 0)
+#     KNITRO.KN_set_param(kc, "outlev", 0)
+#     KNITRO.KN_set_param(kc, "gradopt", 2)
+#     KNITRO.KN_set_param(kc, "hessopt", 2)
+#     KNITRO.KN_set_param(kc, "mip_numthreads", 1)
+#     # END:   Some specific parameter settings
+
+#     function evalF_evalGA(kc, cb, evalRequest, evalResult, userParams)
+#         x = evalRequest.x
+#         evalRequestCode = evalRequest.evalRequestCode
+
+#         if evalRequestCode == KNITRO.KN_RC_EVALFC
+#             # Evaluate nonlinear objective
+#             evalResult.obj[1] = x[1]^2 * x[3] + x[2]^3 * x[3]^2
+#         elseif evalRequestCode == KNITRO.KN_RC_EVALGA
+#             evalResult.objGrad[1] = 2 * x[1] * x[3]
+#             evalResult.objGrad[2] = 3 * x[2]^2 * x[3]^2
+#             evalResult.objGrad[3] = x[1]^2 + 2 * x[2]^3 * x[3]
+#         else
+#             return KNITRO.KN_RC_CALLBACK_ERR
+#         end
+#         return 0
+#     end
+
+#     # Define objective goal
+#     objGoal = KNITRO.KN_OBJGOAL_MAXIMIZE
+#     KNITRO.KN_set_obj_goal(kc, objGoal)
+
+#     # Add the variables and set their bounds.
+#     nV = 3
+#     KNITRO.KN_add_vars(kc, nV)
+#     KNITRO.KN_set_var_lobnds(kc, [0, 0.1, 0])
+#     KNITRO.KN_set_var_upbnds(kc, [0., 2, 2])
+#     KNITRO.KN_set_var_types(kc, [KNITRO.KN_VARTYPE_CONTINUOUS, KNITRO.KN_VARTYPE_INTEGER, KNITRO.KN_VARTYPE_INTEGER])
+
+#     # Define an initial point.
+#     KNITRO.KN_set_var_primal_init_values(kc, [1, 1, 1.5])
+#     KNITRO.KN_set_var_dual_init_values(kc, [1., 1, 1, 1])
+
+#     # Add the constraints and set their lower bounds.
+#     nC = 1
+#     KNITRO.KN_add_cons(kc, nC)
+#     KNITRO.KN_set_con_lobnds(kc, [0.1])
+#     KNITRO.KN_set_con_upbnds(kc, [2 * 2 * 0.99])
+
+#     # Load quadratic structure x1*x2 for the constraint.
+#     KNITRO.KN_add_con_quadratic_struct(kc, 0, 1, 2, 1.0)
+
+#     # Define callback functions.
+#     cb = KNITRO.KN_add_objective_callback(kc, evalF_evalGA)
+#     KNITRO.KN_set_cb_grad(kc, cb, evalF_evalGA)
+
+#     # Define complementarity constraints
+#     KNITRO.KN_set_compcons(kc, [KNITRO.KN_CCTYPE_VARVAR], Int32[0], Int32[1])
+
+#     # Set MIP parameters
+#     KNITRO.KN_set_mip_branching_priorities(kc, Int32[0, 1, 2])
+#     # not compatible with MPEC constraint as a variable cannot be involved in two different complementarity constraints.
+#     # KNITRO.KN_set_mip_intvar_strategies(kc, 2, KNITRO.KN_MIP_INTVAR_STRATEGY_MPEC)
+#     KNITRO.KN_set_mip_node_callback(kc, callback("mip_node"))
+
+#     # Set var, con and obj names
+#     KNITRO.KN_set_var_names(kc, ["myvar1", "myvar2", "myvar3"])
+#     KNITRO.KN_set_con_names(kc, ["mycon1"])
+#     KNITRO.KN_set_obj_name(kc, "myobj")
+
+#     # Set feasibility tolerances
+#     KNITRO.KN_set_var_feastols(kc, [0.1, 0.001, 0.1])
+#     KNITRO.KN_set_con_feastols(kc, [0.1])
+#     KNITRO.KN_set_compcon_feastols(kc, [0.1])
+
+#     # Set finite differences step size
+#     KNITRO.KN_set_cb_relstepsizes(kc, cb, [0.1, 0.001, 0.1])
+
+#     # Solve the problem.
+#     status = KNITRO.KN_solve(kc)
+#     # Test for return codes 0 for optimality, and KN_RC_MIP_EXH_FEAS for all nodes explored, assumed optimal
+#     @test status == 0 || status == KNITRO.KN_RC_MIP_EXH_FEAS
+
+#     @test KNITRO.KN_get_mip_number_nodes(kc) >= 1
+#     @test KNITRO.KN_get_mip_number_solves(kc) >= 1
+#     @test KNITRO.KN_get_mip_relaxation_bnd(kc) ≈ 31.3632000015
+#     @test KNITRO.KN_get_mip_lastnode_obj(kc) ≈ 31.3632000015
+#     @test KNITRO.KN_get_con_values(kc)[1] == 4.0
+#     @test KNITRO.KN_get_mip_incumbent_obj(kc) ≈ 32.0
+#     @test KNITRO.KN_get_mip_incumbent_x(kc) == 0.0
+
+#     KNITRO.KN_free(kc)
+# end
 
 
 @testset "Fifth problem test" begin
@@ -1018,4 +1024,4 @@ end
 
     # Delete the Knitro solver instance.
     KNITRO.KN_free(kc)
-end
\ No newline at end of file
+end