This PR extends the notion of “fixed parameter” of a recursive function
also to parameters that come after varying function. The main benefit is
that we get nicer induction principles.
Before the definition
```lean
def app (as : List α) (bs : List α) : List α :=
match as with
| [] => bs
| a::as => a :: app as bs
```
produced
```lean
app.induct.{u_1} {α : Type u_1} (motive : List α → List α → Prop) (case1 : ∀ (bs : List α), motive [] bs)
(case2 : ∀ (bs : List α) (a : α) (as : List α), motive as bs → motive (a :: as) bs) (as bs : List α) : motive as bs
```
and now you get
```lean
app.induct.{u_1} {α : Type u_1} (motive : List α → Prop) (case1 : motive [])
(case2 : ∀ (a : α) (as : List α), motive as → motive (a :: as)) (as : List α) : motive as
```
because `bs` is fixed throughout the recursion (and can completely be
dropped from the principle).
This is a breaking change when such an induction principle is used
explicitly. Using `fun_induction` makes proof tactics robust against
this change.
The rules for when a parameter is fixed are now:
1. A parameter is fixed if it is reducibly defq to the the corresponding
argument in each recursive call, so we have to look at each such call.
2. With mutual recursion, it is not clear a-priori which arguments of
another function correspond to the parameter. This requires an analysis
with some graph algorithms to determine.
3. A parameter can only be fixed if all parameters occurring in its type
are fixed as well.
This dependency graph on parameters can be different for the different
functions in a recursive group, even leading to cycles.
4. For structural recursion, we kinda want to know the fixed parameters
before investigating which argument to actually recurs on. But once we
have that we may find that we fixed an index of the recursive
parameter’s type, and these cannot be fixed. So we have to un-fix them
5. … and all other fixed parameters that have dependencies on them.
Lean tries to identify the largest set of parameters that satisfies
these criteria.
Note that in a definition like
```lean
def app : List α → List α → List α
| [], bs => bs
| a::as, bs => a :: app as bs
```
the `bs` is not considered fixes, as it goes through the matcher
machinery.
Fixes#7027Fixes#2113
This PR makes `try?` use `fun_induction` instead of `induction … using
foo.induct`. It uses the argument-free short-hand `fun_induction foo` if
that is unambiguous. Avoids `expose_names` if not necessary by simply
trying without first.
This PR gives the `induction` tactic the ability to name hypotheses to
use when generalizing targets, just like in `cases`. For example,
`induction h : xs.length` leads to goals with hypotheses `h : xs.length
= 0` and `h : xs.length = n + 1`. Target handling is also slightly
modified for multi-target induction principles: it used to be that if
any target was not a free variable, all of the targets would be
generalized (thus causing free variables to lose their connection to the
local hypotheses they appear in); now only the non-free-variable targets
are generalized.
This gives `induction` the last basic feature of the mathlib
`induction'` tactic, which has been long-requested. Recent Zulip
discussion:
https://leanprover.zulipchat.com/#narrow/channel/270676-lean4/topic/To.20replace.20.60induction'.20h.20.3A.20f.20x.60/near/499482173
This PR adds new configuration options to `try?`.
- `try? -only` omits `simp only` and `grind only` suggestions
- `try? +missing` enables partial solutions where some subgoals are
"solved" using `sorry`, and must be manually proved by the user.
- `try? (max:=<num>)` sets the maximum number of suggestions produced
(default is 8).
This PR adds support for more complex suggestions in `try?`. Example:
```lean
example (as : List α) (a : α) : concat as a = as ++ [a] := by
try?
```
suggestion
```
Try this: · induction as, a using concat.induct
· rfl
· simp_all
```
This PR adds the `try?` tactic. This is the first draft, but it can
already solve examples such as:
```lean
example (e : Expr) : e.simplify.eval σ = e.eval σ := by
try?
```
in `grind_constProp.lean`. In the example above, it suggests:
```lean
induction e using Expr.simplify.induct <;> grind?
```
In the same test file, we have
```lean
example (σ₁ σ₂ : State) : σ₁.join σ₂ ≼ σ₂ := by
try?
```
and the following suggestion is produced
```lean
induction σ₁, σ₂ using State.join.induct <;> grind?
```
This PR adds the new attributes `[grind =>]` and `[grind <=]` for
controlling pattern selection and minimizing the number of places where
we have to use verbose `grind_pattern` command. It also fixes a bug in
the new pattern selection procedure, and improves the automatic pattern
selection for local lemmas.
The tests `grind_constProp.lean` and `no_grind_constProp.lean` are the
same use case with and without `grind`.
This PR fixes a few `grind` issues exposed by the `grind_constProp.lean`
test.
- Support for equational theorem hypotheses created before invoking
`grind`. Example: applying an induction principle.s
- Support of `Unit`-like types.
- Missing recursion depth checks.
This PR fixes a bug in the pattern selection heuristic used in `grind`.
It was unfolding definitions/abstractions that were not supposed to be
unfolded. See `grind_constProp.lean` for examples affected by this bug.
