The main trick here was transforming Assignment
to contain `Vec<UntypedPattern, Option<Annotation>>`
in a field called patterns. This then meant that I
could remove the `pattern` and `annotation` field
from `Assignment`. The parser handles `=` and `<-`
just fine because in the future `=` with multi
patterns will mean some kind of optimization on tuples.
But, since we don't have that optimization yet, when
someone uses multi patterns with an `=` there will be an
error returned from the type checker right where `infer_seq`
looks for `backpassing`. From there the rest of the work
was in `Project::backpassing` where I only needed to rework
some things to work with a list of patterns instead of just one.
The 3rd kind of assignment kind (Bind) is gone and now reflected through a boolean parameter. Note that this parameter is completely erased by the type-checker so that the rest of the pipeline (i.e. code-generation) doesn't have to make any assumption. They simply can't see a backpassing let or expect.
This is more holistic and less awkward than having monadic bind working only with some pre-defined type. Backpassing work with _any_ function, and can be implemented relatively easily by rewriting the AST on-the-fly.
Also, it is far easier to explain than trying to explain what a monadic bind is, how its behavior differs from type to type and why it isn't generally available for any monadic type.
It might be slightly cleaner and more extensible to change to return a summary, potentially even making track the tests, coverage, etc. so it can be serialized to JSON. But, for now, this is much simpler, and the approach that KtorZ suggested.
We'll piggyback on the tracing capabilities of the VM to provide labelling for prop tests. To ensure we do not interfere with normal traces, we only count traces that starts with a NUL byte as label. That convention is assumed to be known of the companion fuzz library that should then provide the labelling capabilities as a dedicated function.
I've been benchmarking that through the shrink of 'large' lists, and the cache brings about 1.5x speed increase. For small and simple cases, the cache as no visible effects (positive or negative).
rvcas