‘Quis custodiet ipsos custodies? Your grace.’
‘I know that one,’ said Vimes. 'Who watches the watchmen? Me, Mr Pessimal.’
‘Ah, but who watches you, your grace?’ said the inspector, with a brief smile.
‘I do that, too.'
] add https://github.com/MikeInnes/Vimes.jl
] add https://github.com/MikeInnes/CSTParser.jl#location
Simulating a good programmer may be AI-complete, but simulating a bad one is much easier. That's what Vimes does; it makes random, but plausible-looking, changes to your code. Then it runs your test suite. If your tests fail, you're good; if they don't, then the tests are probably missing something important.
Usage:
julia> using Vimes; Vimes.go("../JSON.jl", procs=4) # run 4 tests in parallel
[ Info: (4) Ran 1 tests, precision 100.00%
[ Info: (1) Ran 2 tests, precision 100.00%
...
[ Info: (2) Ran 35 tests, precision 97.14%
Vimes reports the percentage of runs where the tests failed as the precision of the test suite (i.e. 100% is the best possible precision).
In the project folder (here ../JSON.jl
), a .vimes
folder will appear with a .diff
file for every patch found, like this:
@@ -19,7 +19,7 @@ end
function Base.push!(v::PushVector, i)
v.l += 1
- if v.l > length(v.v)
+ if !(v.l > length(v.v))
resize!(v.v, v.l * 2)
end
v.v[v.l] = i
Vimes is powered by the library of patches in src/library.jl
. It's easy to make a new patch; it's just a function which takes an expression and returns either a new expression or nothing
. For example, replacing numeric constants can be done by
function numbers(x)
x isa Number || return
return rand(typeof(x))
end
Note that you do not need to search for numbers inside expressions, since Vimes will automatically apply this function to the whole source tree.
Vimes comes with a set of default patches, Vimes.defaults
. You can supply your own set of patches entirely, or extend the defaults with
Vimes.go(".", [Vimes.defaults..., numbers])