diff --git a/.github/workflows/format_check.yml b/.github/workflows/format_check.yml
new file mode 100644
index 0000000..85b07a5
--- /dev/null
+++ b/.github/workflows/format_check.yml
@@ -0,0 +1,30 @@
+name: format-check
+on:
+  push:
+    branches:
+      - main
+      - release-*
+  pull_request:
+    types: [opened, synchronize, reopened]
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: julia-actions/setup-julia@latest
+        with:
+          version: '1'
+      - uses: actions/checkout@v4
+      - name: Format check
+        shell: julia --color=yes {0}
+        run: |
+          using Pkg
+          Pkg.add(PackageSpec(name="JuliaFormatter", version="2"))
+          using JuliaFormatter
+          format(".", verbose=true)
+          out = String(read(Cmd(`git diff`)))
+          if isempty(out)
+              exit(0)
+          end
+          @error "Some files have not been formatted !!!"
+          write(stdout, out)
+          exit(1)
diff --git a/src/MOI_wrapper.jl b/src/MOI_wrapper.jl
index a1ad957..035b147 100644
--- a/src/MOI_wrapper.jl
+++ b/src/MOI_wrapper.jl
@@ -4,10 +4,7 @@ struct Optimizer{O<:MOI.ModelLike} <: MOI.AbstractOptimizer
     optimizer::O
     reformulation::AbstractComplementarityRelaxation
     function Optimizer(optimizer::MOI.ModelLike)
-        return new{typeof(optimizer)}(
-            optimizer,
-            ScholtesRelaxation(0.0),
-        )
+        return new{typeof(optimizer)}(optimizer, ScholtesRelaxation(0.0))
     end
 end
 
@@ -16,30 +13,21 @@ MOI.empty!(model::Optimizer) = MOI.empty!(model.optimizer)
 
 function MOI.supports(
     model::Optimizer,
-    attr::Union{
-        MOI.AbstractModelAttribute,
-        MOI.AbstractOptimizerAttribute,
-    },
+    attr::Union{MOI.AbstractModelAttribute,MOI.AbstractOptimizerAttribute},
 )
     return MOI.supports(model.optimizer, attr)
 end
 
 function MOI.get(
     model::Optimizer,
-    attr::Union{
-        MOI.AbstractModelAttribute,
-        MOI.AbstractOptimizerAttribute,
-    },
+    attr::Union{MOI.AbstractModelAttribute,MOI.AbstractOptimizerAttribute},
 )
     return MOI.get(model.optimizer, attr)
 end
 
 function MOI.set(
     model::Optimizer,
-    attr::Union{
-        MOI.AbstractModelAttribute,
-        MOI.AbstractOptimizerAttribute,
-    },
+    attr::Union{MOI.AbstractModelAttribute,MOI.AbstractOptimizerAttribute},
     value,
 )
     return MOI.set(model.optimizer, attr, value)
@@ -54,9 +42,7 @@ function MOI.supports_constraint(
 end
 
 function MOI.copy_to(dest::Optimizer, src::MOI.ModelLike)
-    tmp = MOI.Utilities.UniversalFallback(
-        MOI.Utilities.Model{Float64}()
-    )
+    tmp = MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}())
     tmp_index_map = MOI.copy_to(tmp, src)
     reformulate_to_vertical!(tmp)
     reformulate_as_nonlinear_program!(tmp, dest.reformulation)
diff --git a/src/nonlinear.jl b/src/nonlinear.jl
index 53db413..4915e59 100644
--- a/src/nonlinear.jl
+++ b/src/nonlinear.jl
@@ -17,20 +17,28 @@ the complementarity constraints.
 If the complementarity constraints are not in vertical form, an error is thrown.
 
 """
-function reformulate_as_nonlinear_program!(model::MOI.ModelLike, relaxation::AbstractComplementarityRelaxation)
+function reformulate_as_nonlinear_program!(
+    model::MOI.ModelLike,
+    relaxation::AbstractComplementarityRelaxation,
+)
     if !is_vertical(model)
-        error("Complementarity constraints should be reformulated in vertical form before applying nonlinear reformulation")
+        error(
+            "Complementarity constraints should be reformulated in vertical form before applying nonlinear reformulation",
+        )
     end
 
-    cc_cons = MOI.get(model, MOI.ListOfConstraintIndices{MOI.VectorOfVariables, MOI.Complements}())[1]
+    cc_cons = MOI.get(
+        model,
+        MOI.ListOfConstraintIndices{MOI.VectorOfVariables,MOI.Complements}(),
+    )[1]
     fun = MOI.get(model, MOI.ConstraintFunction(), cc_cons)
     set = MOI.get(model, MOI.ConstraintSet(), cc_cons)
     n_comp = div(set.dimension, 2)
 
     ind_cc = []
-    for cc in 1:n_comp
+    for cc = 1:n_comp
         x1 = fun.variables[cc]
-        x2 = fun.variables[cc + n_comp]
+        x2 = fun.variables[cc+n_comp]
         # Get bounds on x2
         lb2, ub2 = MOIU.get_bounds(model, Float64, x2)
         # x2 should have at least one bound, otherwise x1 becomes a fixed variable
@@ -71,7 +79,10 @@ end
 function _relax_complementarity_lower_bound!(
     model::MOI.ModelLike,
     relaxation::ScholtesRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
     lb1, ub1 = MOIU.get_bounds(model, Float64, x1)
     if isinf(lb1)
@@ -80,11 +91,7 @@ function _relax_complementarity_lower_bound!(
         @assert lb1 == 0.0 # ensure we follow MOI's convention
         # TODO: what should we do if ub1 is finite?
     end
-    idc = MOI.add_constraint(
-        model,
-        x1 * (x2 - lb2),
-        MOI.LessThan(relaxation.tau),
-    )
+    idc = MOI.add_constraint(model, x1 * (x2 - lb2), MOI.LessThan(relaxation.tau))
     return [idc]
 end
 
@@ -92,7 +99,10 @@ end
 function _relax_complementarity_upper_bound!(
     model::MOI.ModelLike,
     relaxation::ScholtesRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
     lb1, ub1 = MOIU.get_bounds(model, Float64, x1)
     if isinf(ub1)
@@ -101,11 +111,7 @@ function _relax_complementarity_upper_bound!(
         @assert ub1 == 0.0 # ensure we follow MOI's convention
         # TODO: what should we do if lb1 is finite?
     end
-    idc = MOI.add_constraint(
-        model,
-        x1 * (x2 - ub2),
-        MOI.LessThan(relaxation.tau),
-    )
+    idc = MOI.add_constraint(model, x1 * (x2 - ub2), MOI.LessThan(relaxation.tau))
     return [idc]
 end
 
@@ -113,19 +119,14 @@ end
 function _relax_complementarity_range!(
     model::MOI.ModelLike,
     relaxation::ScholtesRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
     lb1, ub1 = MOIU.get_bounds(model, Float64, x1)
-    idc1 = MOI.add_constraint(
-        model,
-        x1 * (x2 - lb2),
-        MOI.LessThan(relaxation.tau),
-    )
-    idc2 = MOI.add_constraint(
-        model,
-        x1 * (x2 - ub2),
-        MOI.LessThan(relaxation.tau),
-    )
+    idc1 = MOI.add_constraint(model, x1 * (x2 - lb2), MOI.LessThan(relaxation.tau))
+    idc2 = MOI.add_constraint(model, x1 * (x2 - ub2), MOI.LessThan(relaxation.tau))
     return [idc1, idc2]
 end
 
@@ -149,12 +150,9 @@ function _min_eps(a, b, eps)
     return MOI.ScalarNonlinearFunction(
         :-,
         Any[
-            1.0 * a + 1.0 * b ,
-            MOI.ScalarNonlinearFunction(
-                :sqrt,
-                Any[(1.0 * a)^2 + (1.0 * b)^2 + eps^2],
-            )
-        ]
+            1.0*a+1.0*b,
+            MOI.ScalarNonlinearFunction(:sqrt, Any[(1.0*a)^2+(1.0*b)^2+eps^2]),
+        ],
     )
 end
 
@@ -162,12 +160,9 @@ function _max_eps(a, b, eps)
     return MOI.ScalarNonlinearFunction(
         :+,
         Any[
-            1.0 * a + 1.0 * b ,
-            MOI.ScalarNonlinearFunction(
-                :sqrt,
-                Any[(1.0 * a)^2 + (1.0 * b)^2 + eps^2],
-            )
-        ]
+            1.0*a+1.0*b,
+            MOI.ScalarNonlinearFunction(:sqrt, Any[(1.0*a)^2+(1.0*b)^2+eps^2]),
+        ],
     )
 end
 
@@ -175,7 +170,10 @@ end
 function _relax_complementarity_lower_bound!(
     model::MOI.ModelLike,
     relaxation::FischerBurmeisterRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
     lb1, ub1 = MOIU.get_bounds(model, Float64, x1)
     if isinf(lb1)
@@ -196,7 +194,10 @@ end
 function _relax_complementarity_upper_bound!(
     model::MOI.ModelLike,
     relaxation::FischerBurmeisterRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
     lb1, ub1 = MOIU.get_bounds(model, Float64, x1)
     if isinf(ub1)
@@ -217,7 +218,10 @@ end
 function _relax_complementarity_range!(
     model::MOI.ModelLike,
     relaxation::FischerBurmeisterRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
     lb1, ub1 = MOIU.get_bounds(model, Float64, x1)
     idc1 = MOI.add_constraint(
@@ -252,13 +256,12 @@ end
 function _relax_complementarity_lower_bound!(
     model::MOI.ModelLike,
     relaxation::LiuFukushimaRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
-    idc1 = MOI.add_constraint(
-        model,
-        x1 * (x2 - lb2),
-        MOI.LessThan(relaxation.epsilon^2),
-    )
+    idc1 = MOI.add_constraint(model, x1 * (x2 - lb2), MOI.LessThan(relaxation.epsilon^2))
     idc2 = MOI.add_constraint(
         model,
         (x1 + relaxation.epsilon) * (x2 - lb2 + relaxation.epsilon),
@@ -276,13 +279,12 @@ end
 function _relax_complementarity_upper_bound!(
     model::MOI.ModelLike,
     relaxation::LiuFukushimaRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
-    idc1 = MOI.add_constraint(
-        model,
-        x1 * (x2 - ub2),
-        MOI.LessThan(relaxation.epsilon^2),
-    )
+    idc1 = MOI.add_constraint(model, x1 * (x2 - ub2), MOI.LessThan(relaxation.epsilon^2))
     idc2 = MOI.add_constraint(
         model,
         (x1 - relaxation.epsilon) * (x2 - ub2 - relaxation.epsilon),
@@ -325,20 +327,20 @@ function _kanzow_schwarz_relaxation(a, b, eps)
     return MOI.ScalarNonlinearFunction(
         :ifelse,
         Any[
-            MOI.ScalarNonlinearFunction(
-                :>,
-                Any[1.0 * a + 1.0 * b, 2*eps],
-            ),
-            (a - eps) * (b - eps),
-            - 0.5 * ((a - eps)^2 + (b - eps)^2),
-        ]
+            MOI.ScalarNonlinearFunction(:>, Any[1.0*a+1.0*b, 2*eps]),
+            (a-eps)*(b-eps),
+            - 0.5*((a-eps)^2+(b-eps)^2),
+        ],
     )
 end
 
 function _relax_complementarity_lower_bound!(
     model::MOI.ModelLike,
     relaxation::KanzowSchwarzRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
     lb1, ub1 = MOIU.get_bounds(model, Float64, x1)
     if isinf(lb1)
@@ -359,7 +361,10 @@ end
 function _relax_complementarity_upper_bound!(
     model::MOI.ModelLike,
     relaxation::KanzowSchwarzRelaxation,
-    x1, x2, lb2, ub2,
+    x1,
+    x2,
+    lb2,
+    ub2,
 )
     lb1, ub1 = MOIU.get_bounds(model, Float64, x1)
     if isinf(ub1)
@@ -375,4 +380,3 @@ function _relax_complementarity_upper_bound!(
     )
     return [idc]
 end
-
diff --git a/src/vertical.jl b/src/vertical.jl
index 860bbdc..985955a 100644
--- a/src/vertical.jl
+++ b/src/vertical.jl
@@ -1,9 +1,6 @@
 
-const VF = Union{
-    MOI.VectorAffineFunction,
-    MOI.VectorQuadraticFunction,
-    MOI.VectorNonlinearFunction,
-}
+const VF =
+    Union{MOI.VectorAffineFunction,MOI.VectorQuadraticFunction,MOI.VectorNonlinearFunction}
 
 function has_complementarity(model::MOI.ModelLike)
     return any(MOI.get(model, MOI.ListOfConstraintTypesPresent())) do (F, S)
@@ -17,13 +14,16 @@ end
 
 _is_single_variable(::MOI.AbstractScalarFunction) = false
 function _is_single_variable(func::MOI.ScalarAffineFunction)
-    return length(func.terms) == 1 && func.terms[1].coefficient == 1.0 && iszero(func.constant)
+    return length(func.terms) == 1 &&
+           func.terms[1].coefficient == 1.0 &&
+           iszero(func.constant)
 end
 function _is_single_variable(func::MOI.ScalarQuadraticFunction)
-    if (length(func.quadratic_terms) == 0
-        && length(func.affine_terms) == 1
-        && func.affine_terms[1].coefficient == 1.0
-        && iszero(func.constant)
+    if (
+        length(func.quadratic_terms) == 0 &&
+        length(func.affine_terms) == 1 &&
+        func.affine_terms[1].coefficient == 1.0 &&
+        iszero(func.constant)
     )
         return true
     else
@@ -46,10 +46,10 @@ function _parse_complementarity_constraint(fun::MOI.AbstractVectorFunction, n_co
     cc_lhs = MOI.AbstractScalarFunction[]
     cc_rhs = MOI.VariableIndex[]
 
-    for i in 1:n_comp
+    for i = 1:n_comp
         # Parse LHS
         t1 = exprs[i]
-        t2 = exprs[i + n_comp]
+        t2 = exprs[i+n_comp]
         if _is_single_variable(t1)
             push!(cc_lhs, _get_variable(t1))
         else
@@ -62,7 +62,9 @@ function _parse_complementarity_constraint(fun::MOI.AbstractVectorFunction, n_co
             # The RHS should be a variable if we follow MOI's specs
             # TODO: we should decide if we should add support complementarity
             # between expressions (see Issue #2)
-            error("Right-hand-side should be a single variable in complementarity constraints.")
+            error(
+                "Right-hand-side should be a single variable in complementarity constraints.",
+            )
         end
         push!(cc_rhs, _get_variable(t2))
     end
@@ -90,14 +92,14 @@ function reformulate_to_vertical!(model::MOI.ModelLike)
     for (F, S) in contypes
         # Parse only complementarity constraints
         if S == MOI.Complements
-            conindices = MOI.get(model, MOI.ListOfConstraintIndices{F, S}())
+            conindices = MOI.get(model, MOI.ListOfConstraintIndices{F,S}())
             for cidx in conindices
                 fun = MOI.get(model, MOI.ConstraintFunction(), cidx)
                 set = MOI.get(model, MOI.ConstraintSet(), cidx)
                 n_comp = div(set.dimension, 2)
                 if isa(fun, MOI.VectorOfVariables)
                     append!(ind_cc1, fun.variables[1:n_comp])
-                    append!(ind_cc2, fun.variables[n_comp+1:end])
+                    append!(ind_cc2, fun.variables[(n_comp+1):end])
                 elseif isa(fun, VF)
                     # Read each complementarity constraint and get corresponding indices
                     cc_lhs, cc_rhs = _parse_complementarity_constraint(fun, n_comp)
@@ -123,7 +125,9 @@ function reformulate_to_vertical!(model::MOI.ModelLike)
                         end
                     end
                 else
-                    error("Complementary constraints formulated with $(typeof(fun)) are not yet supported")
+                    error(
+                        "Complementary constraints formulated with $(typeof(fun)) are not yet supported",
+                    )
                 end
                 # We delete the complementarity constraints
                 MOI.delete(model, cidx)
diff --git a/test/instances.jl b/test/instances.jl
index c949442..705589a 100644
--- a/test/instances.jl
+++ b/test/instances.jl
@@ -19,7 +19,7 @@ function fletcher_leyffer_ex2_model()
     @variable(model, z[1:2] >= 0)
     @objective(model, Min, z[1] + z[2])
     @constraint(model, z[2]^2 >= 1)
-    @constraint(model, [z[1], z[2]] ∈  MOI.Complements(2))
+    @constraint(model, [z[1], z[2]] ∈ MOI.Complements(2))
     return model
 end
 
@@ -61,8 +61,8 @@ end
 function design_centering_model()
     x0 = [0.0, 0.0, 1.0]
     y0 = [
-        -1.000000000000073   0.2425356250359245                    0;
-                         0   0.9701425001468117   -1.000000000026019
+        -1.000000000000073 0.2425356250359245 0;
+        0 0.9701425001468117 -1.000000000026019
     ]
     l0 = [0.5, 0.5153882031999911, 0.4999999999777709]
     model = Model()
@@ -73,18 +73,21 @@ function design_centering_model()
     @objective(model, Min, -pi*x[3]^2)
     # ... lower level solutions lie in body G
     @constraint(model, g1, -y[1, 1] - y[2, 1]^2 <= 0.0)
-    @constraint(model, g2,  y[1, 2] / 4.0 + y[2, 2] <= 0.75)
+    @constraint(model, g2, y[1, 2] / 4.0 + y[2, 2] <= 0.75)
     @constraint(model, g3, -y[2, 3] <= 1.0)
     # ... first order conditions for 3 lower level problem
     @constraint(model, 1.0 + 2.0 * (y[1, 1] - x[1]) * l[1] == 0.0)
     @constraint(model, 2*y[2, 1] + 2.0 * (y[2, 1] - x[2]) * l[1] == 0.0)
     @constraint(model, -0.25 + 2.0 * (y[1, 2] - x[1]) * l[2] == 0.0)
     @constraint(model, -1.00 + 2.0 * (y[2, 2] - x[2]) * l[2] == 0.0)
-    @constraint(model,  0.00 + 2.0 * (y[1, 3] - x[1]) * l[3] == 0.0)
-    @constraint(model,  1.00 + 2.0 * (y[2, 3] - x[2]) * l[3] == 0.0)
+    @constraint(model, 0.00 + 2.0 * (y[1, 3] - x[1]) * l[3] == 0.0)
+    @constraint(model, 1.00 + 2.0 * (y[2, 3] - x[2]) * l[3] == 0.0)
     # complementarity
-    for k in 1:3
-        @constraint(model, [-(y[1,k] - x[1])^2 - (y[2,k] - x[2])^2 + x[3]^2, l[k]] ∈ MOI.Complements(2))
+    for k = 1:3
+        @constraint(
+            model,
+            [-(y[1, k] - x[1])^2 - (y[2, k] - x[2])^2 + x[3]^2, l[k]] ∈ MOI.Complements(2)
+        )
     end
     return model
 end
@@ -123,8 +126,8 @@ function desilva_model()
     @variable(model, y[1:2])
     @variable(model, 0.0 <= l[1:2])
     @objective(model, Min, x[1]^2 - 2*x[1] + x[2]^2 - 2*x[2] + y[1]^2 + y[2]^2)
-    for i in 1:2
-        @constraint(model, 2.0*y[i] - 2.0*x[i] + 2.0*(y[i] - 1.0) * l[i] == 0.0)
+    for i = 1:2
+        @constraint(model, 2.0*y[i] - 2.0*x[i] + 2.0 * (y[i] - 1.0) * l[i] == 0.0)
         @constraint(model, [0.25 - (y[i] - 1.0)^2, l[i]] ∈ MOI.Complements(2))
     end
     return model
@@ -192,9 +195,13 @@ function hakonsen_model_broken()
     @variable(model, t[1:2] >= 0.0)
     @objective(model, Min, (x[1] * x[2] * l)^(1/3))
     @constraint(model, prices[i=1:2], [(pL - p[i]), x[i]] ∈ MOI.Complements(2))
-    @constraint(model, consum2[i=1:2], [(x[i] * (3.0 * p[i] * (1+t[i])) - 100.0 * pL), p[i]] ∈  MOI.Complements(2))
-    @constraint(model, L*pL == sum(x[i] * p[i] for i in 1:2) + l*pL + G)
-    @constraint(model, revenue, sum(p[i] * t[i] * x[i] for i in 1:2) >= G)
+    @constraint(
+        model,
+        consum2[i=1:2],
+        [(x[i] * (3.0 * p[i] * (1+t[i])) - 100.0 * pL), p[i]] ∈ MOI.Complements(2)
+    )
+    @constraint(model, L*pL == sum(x[i] * p[i] for i = 1:2) + l*pL + G)
+    @constraint(model, revenue, sum(p[i] * t[i] * x[i] for i = 1:2) >= G)
     return model
 end
 
@@ -216,12 +223,12 @@ function qpec2_model()
     @variable(model, x[1:n], start=1.0)
     @variable(model, y[1:m] >= 0.0, start=1.0)
     @variable(model, s[1:n] >= 0.0)
-    @objective(model, Min, sum((x[i] + rr)^2 for i in 1:n) + sum((y[j] + ss)^2 for j in 1:m))
+    @objective(model, Min, sum((x[i] + rr)^2 for i = 1:n) + sum((y[j] + ss)^2 for j = 1:m))
 
     @constraint(model, [i=1:n], y[i] - x[i] >= 0.0)
     @constraint(model, [i=1:n], [(y[i] - x[i]), y[i]] ∈ MOI.Complements(2))
     # This constraint is degenerate and should be replaced by y = 0
-    @constraint(model, [i=n+1:m], [y[i], y[i]] ∈ MOI.Complements(2))
+    @constraint(model, [i=(n+1):m], [y[i], y[i]] ∈ MOI.Complements(2))
     return model
 end
 
@@ -271,15 +278,25 @@ function water_net_model()
     reservoirs = [:NW, :E]
     consumers = [:CC, :W, :SW, :S, :SE, :N]
     arcs = [
-        (:NW ,  :W), (:NW , :CC), (:NW ,  :N),
-        (:E  ,  :N), (:E  , :CC), (:E  ,  :S), (:E  , :SE),
-        (:CC ,  :W), (:CC , :SW), (:CC ,  :S), (:CC ,  :N),
-        (:S  , :SE), (:S  , :SW), (:SW ,  :W),
+        (:NW, :W),
+        (:NW, :CC),
+        (:NW, :N),
+        (:E, :N),
+        (:E, :CC),
+        (:E, :S),
+        (:E, :SE),
+        (:CC, :W),
+        (:CC, :SW),
+        (:CC, :S),
+        (:CC, :N),
+        (:S, :SE),
+        (:S, :SW),
+        (:SW, :W),
     ]
-    supply = Dict{Symbol, Float64}(:NW => 2.5, :E => 6.0)
-    wcost = Dict{Symbol, Float64}(:NW => 0.2, :E => 0.17)
-    pcost = Dict{Symbol, Float64}(:NW => 1.02, :E => 1.02)
-    demand = Dict{Symbol, Float64}(
+    supply = Dict{Symbol,Float64}(:NW => 2.5, :E => 6.0)
+    wcost = Dict{Symbol,Float64}(:NW => 0.2, :E => 0.17)
+    pcost = Dict{Symbol,Float64}(:NW => 1.02, :E => 1.02)
+    demand = Dict{Symbol,Float64}(
         :NW => 0.0,
         :E => 0.0,
         :CC => 1.212,
@@ -289,35 +306,35 @@ function water_net_model()
         :SE => 0.252,
         :N => 0.456,
     )
-    height = Dict{Symbol, Float64}(
+    height = Dict{Symbol,Float64}(
         :NW => 6.50,
-        :E  => 3.25,
+        :E => 3.25,
         :CC => 3.02,
-        :W  => 5.16,
+        :W => 5.16,
         :SW => 4.20,
-        :S  => 1.50,
+        :S => 1.50,
         :SE => 0.00,
-        :N  => 6.30,
+        :N => 6.30,
     )
-    x = Dict{Symbol, Float64}(
-        :NW =>  1200,
-        :E  =>  4000,
-        :CC =>  2000,
-        :W  =>   750,
-        :SW =>   900,
-        :S  =>  2000,
-        :SE =>  4000,
-        :N  =>  3700,
+    x = Dict{Symbol,Float64}(
+        :NW => 1200,
+        :E => 4000,
+        :CC => 2000,
+        :W => 750,
+        :SW => 900,
+        :S => 2000,
+        :SE => 4000,
+        :N => 3700,
     )
-    y = Dict{Symbol, Float64}(
-        :NW =>  3600,
-        :E  =>  2200,
-        :CC =>  2300,
-        :W  =>  2400,
-        :SW =>  1200,
-        :S  =>  1000,
-        :SE =>   900,
-        :N  =>  3500,
+    y = Dict{Symbol,Float64}(
+        :NW => 3600,
+        :E => 2200,
+        :CC => 2300,
+        :W => 2400,
+        :SW => 1200,
+        :S => 1000,
+        :SE => 900,
+        :N => 3500,
     )
 
     dist = Dict((i, j) => sqrt((x[i] - x[j])^2 + (y[i] - y[j])^2) for (i, j) in arcs)
@@ -350,8 +367,10 @@ function water_net_model()
     @variable(model, 0 <= s[i in reservoirs] <= supply[i], start=rr*supply[i])
 
     @objective(
-        model, Min,
-        sum(s[i] * pcost[i] * (h[i] - height[i]) + s[i] * wcost[i] for i in reservoirs) / r +
+        model,
+        Min,
+        sum(s[i] * pcost[i] * (h[i] - height[i]) + s[i] * wcost[i] for i in reservoirs) /
+        r +
         dprc * sum(dist[(i, j)] * d[(i, j)]^cpow for (i, j) in arcs) +
         sum(qp[(i, j)] + qn[(i, j)] for (i, j) in arcs),
     )
@@ -367,7 +386,8 @@ function water_net_model()
     @constraint(
         model,
         loss[(i, j) in arcs],
-        h[i] - h[j] == hloss * dist[(i, j)] * (qp[(i, j)]^2 - qn[(i, j)]^2) / (d[(i, j)]^dpow),
+        h[i] - h[j] ==
+        hloss * dist[(i, j)] * (qp[(i, j)]^2 - qn[(i, j)]^2) / (d[(i, j)]^dpow),
     )
     # ... complementarity
     @constraint(model, [(i, j) in arcs], [qp[(i, j)], qn[(i, j)]] ∈ MOI.Complements(2))
diff --git a/test/runtests.jl b/test/runtests.jl
index 7a182e2..b1d7fb6 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -43,9 +43,8 @@ function nonlinear_test_reformulated_model()
     return model
 end
 
-expected_models = Dict(
-    Instances.fletcher_leyffer_ex1_model => fletcher_leyffer_ex1_nonlinear_model,
-)
+expected_models =
+    Dict(Instances.fletcher_leyffer_ex1_model => fletcher_leyffer_ex1_nonlinear_model)
 
 function test_model(model_func)
     model = model_func()
@@ -110,4 +109,4 @@ end
 
     @test JuMP.objective_value(model) ≈ 0.5 atol=1e-7
     @test JuMP.value.(model[:z]) ≈ [0.5, 0.5] atol=1e-7
-end
\ No newline at end of file
+end