LL(1) Parsing -- First(A) with Recursive First Alternatives - parsing

How would I apply the FIRST() rule on a production such as :
A -> AAb | Ab | s
where A is a non-terminal, and b,s are terminals.
FIRST(A) of alternatives 1 & 2 would be A again, but such would end in infinite applications of FIRST, since I need a terminal to get the FIRST set?

To compute FIRST sets, you typically perform a fixed-point iteration. That is, you start off with a small set of values, then iteratively recompute FIRST sets until the sets converge.
In this case, you would start off by noting that the production A → s means that FIRST(A) must contain {s}. So initially you set FIRST(A) = {s}.
Now, you iterate across each production of A and update FIRST based on the knowledge of the FIRST sets you've computed so far. For example, the rule
A → AAb
Means that you should update FIRST(A) to include all elements of FIRST(AAb). This causes no change to FIRST(A). You then visit
A → Ab
You again update FIRST(A) to include FIRST(Ab), which is again a no-op. Finally, you visit
A → s
And since FIRST(A) already contains s, this causes no change.
Since nothing changed on this iteration, you would end up with FIRST(A) = {s}, which is indeed correct because any derivation starting at A ultimately will produce an s as its first character.
For more information, you might find these lecture slides useful (here's part two). They describe in detail how top-down parsing works and how to iteratively compute FIRST sets.
Hope this helps!

My teaching notes are in Spanish, but the algorithms are in English. This is one way to calculate FIRST:
foreach a ∈ Σ do
F(a) := {a}
for each A ∈ N do
if A→ε ∈ P then
F(A) := {ε}
else
F(A) := ∅
repeat
for each A ∈ N do
F'(A) := F(A)
for each A → X1X2...Xn ∈ P do
if n > 0 then
F(A) := F(A) ∪ F'(X1) ⋅k F'(X2) ⋅k ... ⋅k F'(Xn)
until F(A) = F'(A) forall A ∈ N
FIRSTk(X) := F(X) forall X ∈ (Σ ∪ N)
Σ is the alphabet (terminals), N is the set of non-terminals, P is the set of productions (rules), ε is the null string, and ⋅k is concatenation trimmed to k places. Note that ∅ ⋅k x = ∅, and that concatenating two sets produces the concatenation of the elements in the Cartesian product.
The easiest way to calculate FIRST sets by hand is by using one table per algorithm iteration.
F(A) = ∅
F'(A) = F(A) ⋅1 F(A) .1 F(b) U F(A) .1 F(b) U F(s)
F'(A) = ∅ ⋅1 ∅ ⋅1 {b} U ∅ ⋅1 {b} U {s}
F'(A) = ∅ U ∅ U {s}
F'(A) = {s}
F''(A) = F'(A) ⋅1 F'(A) .1 F'(b) U F'(A) .1 F'(b) U F'(s)
F''(A) = {s} ⋅1 {s} ⋅1 {b} U {s} ⋅1 {b} U {s}
F''(A) = {s} U {s} U {s}
F''(A) = {s}
And we're done, because F' = F'', so FIRST = F'', and FIRST(A) = {s}.

your grammar rule has left recursion as you already realized and LL parsers are not able to parse grammars with left recursion.
So you need to get rid of left recursion first and then you should be able to compute the first set for the rule.

Related

How to prove element addition is injective for a cubical finite multi set?

I'm playing around with the type of finite multisets as defined in the cubical standard library here:
https://github.com/agda/cubical/blob/0d272ccbf6f3b142d1b723cead28209444bc896f/Cubical/HITs/FiniteMultiset/Base.agda#L15
data FMSet (A : Type ℓ) : Type ℓ where
[] : FMSet A
_∷_ : (x : A) → (xs : FMSet A) → FMSet A
comm : ∀ x y xs → x ∷ y ∷ xs ≡ y ∷ x ∷ xs
trunc : isSet (FMSet A)
I was able to reproduce the proofs for count extensionality and one of my lemmas I showed that you can remove a element from both sides of an equality and keep the equality.
It was similar to this one: https://github.com/agda/cubical/blob/0d272ccbf6f3b142d1b723cead28209444bc896f/Cubical/HITs/FiniteMultiset/Properties.agda#L183
remove1-≡-lemma : ∀ {a} {x} xs → a ≡ x → xs ≡ remove1 a (x ∷ xs)
remove1-≡-lemma {a} {x} xs a≡x with discA a x
... | yes _ = refl
... | no a≢x = ⊥.rec (a≢x a≡x)
My proofs weren't using the same syntax but in the core libraries syntax it was
cons-path-lemma : ∀ {x} xs ys → (x ∷ xs) ≡ (x ∷ ys) → xs ≡ ys
where the proof is using remove1-≡-lemma path composed on both side of a path which is the argument path functionally composed with remove1 x.
This requires the type of the values to have decidable equality as remove1 doesn't make sense without it. But the lemma itself doesn't mention decidable equality, and so I thought I would try to prove it without having that as a hypothesis. Its now a week later and I'm at my wits end because this seems so 'obvious' but so stubborn to prove.
I'm thinking that my intuition about this being provable may be coming from my classical math background, and so it doesn't follow constructively/contiuously.
So my question is: Is this provable with no assumptions on the element type? If so what would the general structure of the proof look like, I have had trouble getting proofs that want to induct over the two FMSets simultaneously to work (as I'm mostly guessing when trying to get paths to line up as necessary). If it is not provable with no assumptions, is it possible to show that it is equivalent in some form to the necessary assumptions?
I can't offer a proof but an argument why it should be provable without assuming decidability. I think finite multisets can be represented as functions Fin n -> A and equality between multisets f and g is given by a permutation phi : Fin n ~ Fin n, (that is invertible functions on Fin n) such that f o phi = g. Now
(a :: f) 0 = a
(a :: f) (suc i) = f i
If phi : Fin (suc n) ~ Fin (suc n) proves that a :: f = a :: g you can construct a psi : Fin n ~ Fin n which proves that f = g. If phi 0 = 0 then psi n = phi (suc n) otherwise you have to obtain psi by assigning phi^-1 0 to phi 0. However this case analysis is on Fin n.
I think representing the permutation group by swapping adjacent elements is just an inconvenient representation for this problem.

How to prove that the halving function over positive rationals always has an existential?

open import Data.Nat using (ℕ;suc;zero)
open import Data.Rational
open import Data.Product
open import Relation.Nullary
open import Data.Bool using (Bool;false;true)
halve : ℕ → ℚ
halve zero = 1ℚ
halve (suc p) = ½ * halve p
∃-halve : ∀ {a b} → 0ℚ < a → a < b → ∃[ p ] (halve p * b < a)
∃-halve {a} {b} 0<a a<b = h 1 where
h : ℕ → ∃[ p ] (halve p * b < a)
h p with halve p * b <? a
h p | .true because ofʸ b'<a = p , b'<a
h p | .false because ofⁿ ¬b'<a = h (suc p)
The termination checker fails in that last case and it is no wonder as the recursion obviously is neither well funded nor structural. Nevertheless, I am quite sure this should be valid, but have no idea how to prove the termination of ∃-halve. Any advice for how this might be done?
When you’re stuck on a lemma like this, a good general principle is to forget Agda and its technicalities for a minute. How would you prove it in ordinary human-readable mathematical prose, in as elementary way as possible?
Your “iterated halving” function is computing b/(2^p). So you’re trying to show: for any positive rationals a, b, there is some natural p such that b/(2^p) < a. This inequality is equivalent to 2^p > b/a. You can break this down into two steps: find some natural n ≥ b/a, and then find some p such that 2^p > n.
As mentioned in comments, a natural way to do find such numbers would be to implement the ceiling function and the log_2 function. But as you say, those would be rather a lot of work, and you don’t need them here; you just need existence of such numbers. So you can do the above proof in three steps, each of which is elementary enough for a self-contained Agda proof, requiring only very basic algebraic facts as background:
Lemma 1: for any rational q, there’s some natural n > q. (Proof: use the definition of the ordering on rationals, and a little bit of algebra.)
Lemma 2: for any natural n, there’s some natural p such that 2^p > n. (Proof: take e.g. p := (n+1); prove by induction on n that 2^(n+1) > n.)
Lemma 3: these together imply the theorem about halving that you wanted. (Proof: a bit of algebra with rationals, showing that the b/(2^p) < a is equivalent to 2^p > b/a, and showing that your iterated-halving function gives b/2^p.)

Provable coherence in OTT

I'm playing with observational type theory.
Here is equality of π-types (π is the lowercase Π, i.e. π A B is the code for (x : A) -> B x) defined mutually with coercions:
π A₁ B₁ ≃ π A₂ B₂ = σ (A₂ ≃ A₁) λ P -> π _ λ x -> B₁ (coerce P x) ≃ B₂ x
and equality of functions defined accordingly (σ is the lowercase Σ):
_≅_ {A = π A₁ B₁} {π A₂ B₂} f₁ f₂ = σ (A₂ ≃ A₁) λ P -> π _ λ x -> f₁ (coerce P x) ≅ f₂ x
So instead of "equal functions map equal inputs to equal outputs" we have "equal functions map definitionally equal inputs to equal outputs".
In this setting coherence
coerce : ∀ {α β} {A : Univ α} {B : Univ β} -> ⟦ A ≃ B ⟧ᵀ -> ⟦ A ⟧ᵀ -> ⟦ B ⟧ᵀ
coherence : ∀ {α β} {A : Univ α} {B : Univ β}
-> (P : ⟦ A ≃ B ⟧ᵀ) -> (x : ⟦ A ⟧ᵀ) -> ⟦ x ≅ coerce P x ⟧ᵀ
(Univ 0 is Prop, Univ (suc α) is Type α)
is provable. The only thing I needed to postulate is
postulate ≃-refl : ∀ {α} -> (A : Univ α) -> ⟦ A ≃ A ⟧ᵀ
But we can tweak equality to handle A ≃ A as a special case (I think, trustMe needs a friend _≟_ : ∀ {α} {A : Set α} (x y : A) -> Maybe (x ≡ y)).
We still need to postulate something to define subst and other stuff.
Did I miss something? Do we lose any irrelevance? It seems suspicious to mention type equality in the definition of equality of functions. Do we lose much by restricting inputs of equal functions to be definitionally equal? Is there anything good about having strongly normalizing coherence or it doesn't matter, since it's computationally irrelevant anyway?
The code (I ignored positivity, termination and cumulativity issues altogether).
Firstly, thanks for asking about Observational Type Theory. Secondly, what you've done here does seem to hang together, even though it has things in different places from where Thorsten Altenkirch, Wouter Swierstra and I put them in our version of the story. Thirdly, it's no surprise (at least not to me) that coherence is derivable, leaving reflexivity the only postulate. That's true of our OTT as well, and Wouter did the proofs in Agda 1, back when we wrote that paper. Proof irrelevance and the shortness of life meant I didn't port his proofs to Agda 2.
If you've missed anything, it's lurking in your remark
We still need to postulate something to define subst and other stuff.
If you have some P : X -> Set, some a, b : X and some q : a = b, you expect to get a function in P a -> P b. The "equal functions take equal inputs to equal outputs" formulation gives you that, as refl P : P = P, so from q, we can deduce P a = P b. Your "equal functions take a given input to equal outputs" formulation does not allow you to let q bridge the gap from a to b.
In the presence of refl and subst, "two equal inputs" amounts to the same thing as "one input used in two places". It seems to me that you've moved the work into whatever else you need to get subst. Depending on how lazy your definition of coerce is (and that's how you get proof irrelevance), you will need only a postulate.
With your particular formulation, you might even get away with a homogeneous value equality. If you're fixing type gaps with coercions rather than equations, you might save yourself some trouble (and maybe get rid of that equation on the domain type in function equality). Of course, in that case, you'd need to think about how to replace the statement of coherence.
We tried quite hard to keep coercion out of the definition of equality, to retain some sort of symmetry, and to keep type equations out of value equations, mostly to have less to think about at one go. It's interesting to see that at least some parts of the construction might get easier with "a thing and its coercion" replacing "two equal things".

Non trivial negation in agda

All negations, i.e. conclusions of the form A -> Bottom in agda that I've seen came from absurd pattern matchings. Are there any other cases where it's possible to get negation in agda? Are there any other cases in dependent type theory where it's possible?
Type theories usually don't have a notion of pattern matching (and by extension absurd patterns) and yet they can prove negation of the sort you are describing.
First of all, we'll have to look at data types. Without pattern matching, you characterise them by introduction and elimination rules. Introduction rules are basically constructors, they tell you how to construct a value of that type. On the other hand, elimination rules tell you how to use a value of that type. There are also associated computation rules (β-reduction and sometimes η-reduction), but we needn't deal with those now.
Elimination rules look a bit like folds (at least for positive types). For example, here's how an elimination rule for natural numbers would look like in Agda:
ℕ-elim : ∀ {p} (P : ℕ → Set p)
(s : ∀ {n} → P n → P (suc n))
(z : P 0) →
∀ n → P n
ℕ-elim P s z zero = z
ℕ-elim P s z (suc n) = s (ℕ-elim P s z n)
While Agda does have introduction rules (constructors), it doesn't have elimination rules. Instead, it has pattern matching and as you can see above, we can recover the elimination rule with it. However, we can also do the converse: we can simulate pattern matching using elimination rules. Truth be told, it's usually much more inconvenient, but it can be done - the elimination rule mentioned above basically does pattern matching on the outermost constructor and if we need to go deeper, we can just apply the elimination rule again.
So, we can sort of simulate pattern matching. What about absurd patterns? As an example, we'll take fourth Peano axiom:
peano : ∀ n → suc n ≡ zero → ⊥
However, there's a trick involved (and in fact, it's quite crucial; in Martin-Löf's type theory without universes you cannot do it without the trick, see this paper). We need to construct a function that will return two different types based on its arguments:
Nope : (m n : ℕ) → Set
Nope (suc _) zero = ⊥
Nope _ _ = ⊤
If m ≡ n, we should be able to prove that Nope m n holds (is inhabitated). And indeed, this is quite easy:
nope : ∀ m n → m ≡ n → Nope m n
nope zero ._ refl = _
nope (suc m) ._ refl = _
You can now sort of see where this is heading. If we apply nope to the "bad" proof that suc n ≡ zero, Nope (suc n) zero will reduce to ⊥ and we'll get the desired function:
peano : ∀ n → suc n ≡ zero → ⊥
peano _ p = nope _ _ p
Now, you might notice that I cheated a bit. I used pattern matching even though I said earlier that these type theories don't come with pattern matching. I'll remedy that for the next example, but I suggest you try to prove peano without pattern matching on the numbers (use ℕ-elim given above); if you really want a hardcore version, do it without pattern matching on equality as well and use this eliminator instead:
J : ∀ {a p} {A : Set a} (P : ∀ (x : A) y → x ≡ y → Set p)
(f : ∀ x → P x x refl) → ∀ x y → (p : x ≡ y) → P x y p
J P f x .x refl = f x
Another popular absurd pattern is on something of type Fin 0 (and from this example, you'll get the idea how other such absurd matches could be simulated). So, first of all, we'll need eliminator for Fin.
Fin-elim : ∀ {p} (P : ∀ n → Fin n → Set p)
(s : ∀ {n} {fn : Fin n} → P n fn → P (suc n) (fsuc fn))
(z : ∀ {n} → P (suc n) fzero) →
∀ {n} (fn : Fin n) → P n fn
Fin-elim P s z fzero = z
Fin-elim P s z (fsuc x) = s (Fin-elim P s z x)
Yes, the type is really ugly. Anyways, we're going to use the same trick, but this time, we only need to depend on one number:
Nope : ℕ → Set
Nope = ℕ-elim (λ _ → Set) (λ _ → ⊤) ⊥
Note that is equivalent to:
Nope zero = ⊥
Nope (suc _) = ⊤
Now, notice that both cases for the eliminator above (that is, s and z case) return something of type P (suc n) _. If we choose P = λ n _ → Nope n, we'll have to return something of type ⊤ for both cases - but that's easy! And indeed, it was easy:
bad : Fin 0 → ⊥
bad = Fin-elim (λ n _ → Nope n) (λ _ → _) _
The last thing you might be wondering about is how do we get value of any type from ⊥ (known as ex falso quodlibet in logic). In Agda, we obviously have:
⊥-elim : ∀ {w} {Whatever : Set w} → ⊥ → Whatever
⊥-elim ()
But it turns out that this is precisely the eliminator for ⊥, so it is given when defining this type in type theory.
Are you asking for something like
open import Relation.Nullary
→-transposition : {P Q : Set} → (P → Q) → ¬ Q → ¬ P
→-transposition p→q ¬q p = ¬q (p→q p)
?

Using multiple EqReasoning instantiations conveniently

Is there a way to conveniently use multiple instantiations of EqReasoning where the underlying Setoid is not necessarily semantic equality (i.e. ≡-Reasoning cannot be used)? The reason that ≡-Reasoning is convenient is that the type argument is implicit and it uniquely determines the Setoid in use by automatically selecting semantic equality. When using arbitrary Setoids there is no such unique selection. However a number of structures provide a canonical way to lift a Setoid:
Data.Maybe and Data.Covec have a setoid member.
Data.Vec.Equality.Equality provides enough definitions to write a canonical Setoid lifting for Vec as well. Interestingly there is also is a slightly different equality available at Relation.Binary.Vec.Pointwise, but it does not provide a direct lifting either albeit implementing all the necessary bits.
Data.List ships a Setoid lifting in Relation.Binary.List.Pointwise.
Data.Container also knows how to lift a Setoid.
By using any of these structures, one automatically gets to work with multiple Setoids even if one started out with one. When proofs use these structures (multiple of them in a single proof), it becomes difficult to write down the proof, because EqReasoning must be instantiated for all of them even though each particular Setoid is kind of obvious. This can be done by renaming begin_, _≈⟨_⟩_ and _∎, but I don't consider this renaming convenient.
Consider for example, a proof in the Setoid of Maybe where a sequence of arguments needs to be wrapped in Data.Maybe.Eq.just (think cong just) or a proof in an arbitrary Setoid that temporarily needs to wrap things in a just constructor exploiting its injectivity.
Normally, the only way Agda can pick something for you is when it is uniquely determined by the context. In the case of EqReasoning, there isn't usually enough information to pin down the Setoid, even worse actually: you could have two different Setoids over the same Carrier and _≈_ (consider for example two definitionally unequal proofs of transitivity in the isEquivalence field).
However, Agda does allow special form of implicit arguments, which can be filled as long as there is only one value of the desired type. These are known as instance arguments (think instance as in Haskell type class instances).
To demonstrate roughly how this works:
postulate
A : Set
a : A
Now, instance arguments are wrapped in double curly braces {{}}:
elem : {{x : A}} → A
elem {{x}} = x
If we decide to later use elem somewhere, Agda will check for any values of type A in scope and if there's only one of them, it'll fill that one in for {{x : A}}. If we added:
postulate
b : A
Agda will now complain that:
Resolve instance argument _x_7 : A. Candidates: [a : A, b : A]
Because Agda already allows you to perform computations on type level, instance arguments are deliberately limited in what they can do, namely Agda won't perform recursive search to fill them in. Consider for example:
eq : ... → IsEquivalence _≈_ → IsEquivalence (Eq _≈_)
where Eq is Data.Maybe.Eq mentioned in your question. When you then require Agda to fill in an instance argument of a type IsEquivalence (Eq _≈_), it won't try to find something of type IsEquivalence _≈_ and apply eq to it.
With that out of the way, let's take a look at what could work. However, bear in mind that all this stands on unification and as such you might need to push it in the right direction here and there (and if the types you are dealing with become complex, unification might require you to give it so many directions that it won't be worth it in the end).
Personally, I find instance arguments a bit fragile and I usually avoid them (and from a quick check, it would seem that so does the standard library), but your experience might vary.
Anyways, here we go. I constructed a (totally nonsensical) example to demonstrate how to do it. Some boilerplate first:
open import Data.Maybe
open import Data.Nat
open import Relation.Binary
import Relation.Binary.EqReasoning as EqR
To make this example self-contained, I wrote some kind of Setoid with natural numbers as its carrier:
data _≡ℕ_ : ℕ → ℕ → Set where
z≡z : 0 ≡ℕ 0
s≡s : ∀ {m n} → m ≡ℕ n → suc m ≡ℕ suc n
ℕ-setoid : Setoid _ _
ℕ-setoid = record
{ _≈_ = _≡ℕ_
; isEquivalence = record
{ refl = refl
; sym = sym
; trans = trans
}
}
where
refl : Reflexive _≡ℕ_
refl {zero} = z≡z
refl {suc _} = s≡s refl
sym : Symmetric _≡ℕ_
sym z≡z = z≡z
sym (s≡s p) = s≡s (sym p)
trans : Transitive _≡ℕ_
trans z≡z q = q
trans (s≡s p) (s≡s q) = s≡s (trans p q)
Now, the EqReasoning module is parametrized over a Setoid, so usually you do something like this:
open EqR ℕ-setoid
However, we'd like to have the Setoid parameter to be implicit (instance) rather than explicit, so we define and open a dummy module:
open module Dummy {c ℓ} {{s : Setoid c ℓ}} = EqR s
And we can write this simple proof:
idʳ : ∀ n → n ≡ℕ (n + 0)
idʳ 0 = z≡z
idʳ (suc n) = begin
suc n ≈⟨ s≡s (idʳ n) ⟩
suc (n + 0) ∎
Notice that we never had to specify ℕ-setoid, the instance argument picked it up because it was the only type-correct value.
Now, let's spice it up a bit. We'll add Data.Maybe.setoid into the mix. Again, because instance arguments do not perform a recursive search, we'll have to define the setoid ourselves:
Maybeℕ-setoid = setoid ℕ-setoid
_≡M_ = Setoid._≈_ Maybeℕ-setoid
I'm going to postulate few stupid things just to demonstrate that Agda indeed picks correct setoids:
postulate
comm : ∀ m n → (m + n) ≡ℕ (n + m)
eq0 : ∀ n → n ≡ℕ 0
eq∅ : just 0 ≡M nothing
lem : ∀ n → just (n + 0) ≡M nothing
lem n = begin
just (n + 0) ≈⟨ just
(begin
n + 0 ≈⟨ comm n 0 ⟩
n ≈⟨ eq0 n ⟩
0 ∎
)⟩
just 0 ≈⟨ eq∅ ⟩
nothing ∎
I figured an alternative to the proposed solution using instance arguments that slightly bends the requirements, but fits my purpose. The major burden in the question was having to explicitly open EqReasoning multiple times and especially having to invent new names for the contained symbols. A slight improvement would be to pass the correct Setoid once per relation proof. In other words passing it to begin_ or _∎ somehow. Then we could make the Setoid implicit for all the other functions!
import Relation.Binary.EqReasoning as EqR
import Relation.Binary using (Setoid)
module ExplicitEqR where
infix 1 begin⟨_⟩_
infixr 2 _≈⟨_⟩_ _≡⟨_⟩_
infix 2 _∎
begin⟨_⟩_ : ∀ {c l} (X : Setoid c l) → {x y : Setoid.Carrier X} → EqR._IsRelatedTo_ X x y → Setoid._≈_ X x y
begin⟨_⟩_ X p = EqR.begin_ X p
_∎ : ∀ {c l} {X : Setoid c l} → (x : Setoid.Carrier X) → EqR._IsRelatedTo_ X x x
_∎ {X = X} = EqR._∎ X
_≈⟨_⟩_ : ∀ {c l} {X : Setoid c l} → (x : Setoid.Carrier X) → {y z : Setoid.Carrier X} → Setoid._≈_ X x y → EqR._IsRelatedTo_ X y z → EqR._IsRelatedTo_ X x z
_≈⟨_⟩_ {X = X} = EqR._≈⟨_⟩_ X
_≡⟨_⟩_ : ∀ {c l} {X : Setoid c l} → (x : Setoid.Carrier X) → {y z : Setoid.Carrier X} → x ≡ y → EqR._IsRelatedTo_ X y z → EqR._IsRelatedTo_ X x z
_≡⟨_⟩_ {X = X} = EqR._≡⟨_⟩_ X
Reusing the nice example from Vitus answer, we can write it:
lem : ∀ n → just (n + 0) ≡M nothing
lem n = begin⟨ Data.Maybe.setoid ℕ-setoid ⟩
just (n + 0) ≈⟨ just
(begin⟨ ℕ-setoid ⟩
n + 0 ≈⟨ comm n 0 ⟩
n ≈⟨ eq0 n ⟩
0 ∎
)⟩
just 0 ≈⟨ eq∅ ⟩
nothing ∎
where open ExplicitEqR
One still has to mention the Setoids in use, to avoid the use of instance arguments as presented by Vitus. However the technique makes it significantly more convenient.

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