Try #262:

Author: bors[bot]

test/compiler.jl

@@ -252,11 +252,11 @@ end
         vi2 = VarInfo(f2())
         vi3 = VarInfo(f3())
         @test haskey(vi1.metadata, :y)
-        @test vi1.metadata.y.vns[1] == VarName{:y}()
+        @test vi1.metadata.y.vns[1] == @varname(y)
         @test haskey(vi2.metadata, :y)
-        @test vi2.metadata.y.vns[1] == VarName{:y}(((2,), (Colon(), 1)))
+        @test vi2.metadata.y.vns[1] == @varname(y[2][:, 1])
         @test haskey(vi3.metadata, :y)
-        @test vi3.metadata.y.vns[1] == VarName{:y}(((1,),))
+        @test vi3.metadata.y.vns[1] == @varname(y[1])
     end
     @testset "custom tilde" begin
         @model demo() = begin
@@ -326,22 +326,22 @@ end
         m = demo2(missing, missing)
         vi = VarInfo(m)
         ks = keys(vi)
-        @test VarName(:x) ∈ ks
-        @test VarName(:y) ∈ ks
+        @test @varname(x) ∈ ks
+        @test @varname(y) ∈ ks
 
         # Observation in top-level.
         m = demo2(missing, 1.0)
         vi = VarInfo(m)
         ks = keys(vi)
-        @test VarName(:x) ∈ ks
-        @test VarName(:y) ∉ ks
+        @test @varname(x) ∈ ks
+        @test @varname(y) ∉ ks
 
         # Observation in nested model.
         m = demo2(1000.0, missing)
         vi = VarInfo(m)
         ks = keys(vi)
-        @test VarName(:x) ∉ ks
-        @test VarName(:y) ∈ ks
+        @test @varname(x) ∉ ks
+        @test @varname(y) ∈ ks
 
         # Observe all.
         m = demo2(1000.0, 0.5)
@@ -350,13 +350,13 @@ end
         @test isempty(ks)
 
         # Check values makes sense.
-        @model function demo2(x, y)
+        @model function demo3(x, y)
             @submodel demo1(x)
             return y ~ Normal(x)
         end
-        m = demo2(1000.0, missing)
+        m = demo3(1000.0, missing)
         # Mean of `y` should be close to 1000.
-        @test abs(mean([VarInfo(m)[VarName(:y)] for i in 1:10]) - 1000) ≤ 10
+        @test abs(mean([VarInfo(m)[@varname(y)] for i in 1:10]) - 1000) ≤ 10
 
         # Prefixed submodels and usage of submodel return values.
         @model function demo_return(x)
@@ -373,10 +373,10 @@ end
         m = demo_useval(missing, missing)
         vi = VarInfo(m)
         ks = keys(vi)
-        @test VarName(Symbol("sub1.x")) ∈ ks
-        @test VarName(Symbol("sub2.x")) ∈ ks
-        @test VarName(:z) ∈ ks
-        @test abs(mean([VarInfo(m)[VarName(:z)] for i in 1:10]) - 100) ≤ 10
+        @test VarName{Symbol("sub1.x")}() ∈ ks
+        @test VarName{Symbol("sub2.x")}() ∈ ks
+        @test @varname(z) ∈ ks
+        @test abs(mean([VarInfo(m)[@varname(z)] for i in 1:10]) - 100) ≤ 10
 
         # AR1 model. Dynamic prefixing.
         @model function AR1(num_steps, α, μ, σ, ::Type{TV}=Vector{Float64}) where {TV}
@@ -410,7 +410,7 @@ end
         vi = VarInfo(m)
 
         for k in [:α, :μ, :σ, Symbol("ar1_1.η"), Symbol("ar1_2.η")]
-            @test VarName(k) ∈ keys(vi)
+            @test VarName{k}() ∈ keys(vi)
         end
     end