[mindB]

JET.jl does a surprisingly good job of statically checking julia type errors as well as other classes of errors using only type-level code analysis.

https://github.com/aviatesk/JET.jl

It does catch method ambiguities like those shown in this blog post:

  julia> using JET
  
  julia> f(x, y::Int) = x + y
  f (generic function with 2 methods)
  
  julia> f(x::Int, y) = x - y
  f (generic function with 2 methods)
  
  julia> g(x, y) = f(x, y)
  g (generic function with 1 method)
  
  julia> @test_call g(1, 2)
  JET-test failed at REPL[13]:1
    Expression: #= REPL[13]:1 =# JET.@test_call g(1, 2)
    ═════ 1 possible error found ═════
    ┌ @ REPL[12]:1 Main.f(x, y)
    │ no matching method found for call signature (Tuple{typeof(f), Int64, Int64}): Main.f(x::Int64, y::Int64)
    └──────────────
  
  ERROR: There was an error during testing