What are the parsing algorithms for programmed grammars? - parsing

I want to know what are the parsing algorithms used for parsing programmed grammars. Any Links , blogs or anything where i can read about programmed grammars and there parsing algorithms except IEEE research papers ?

I think it's explained well in The power of programmed grammars with graphs from various classes:
A context-free grammar is specified as a quadruple G = (N, T, S, P), where N
is a finite non-empty set called the nonterminal alphabet, T is a finite non-empty set called the terminal alphabet (N ∩ T = ∅), S ∈ N is the start symbol, and P
is a finite subset of N × (N ∪ T)∗ called the set of rules. Rules are also named
as productions.
A programmed grammar (without appearance checking) is a six-tuple G =
(N, T, S, Lab, P, PG) where N , T and S are specified as in a context-free grammar, Lab is an alphabet (of labels), P is a finite set of context-free rules called
the set core productions, and PG is a finite set of triples r = (q, p, σ), where
q ∈ Lab is the label of r, p ∈ P is a context-free production called the core
production of r, and σ is a subset of Lab and is termed the success field of r.
The elements of PG are called the rules of G.
The language L(G) generated by a programmed grammar G specified as above
is defined as the set of all words w ∈ T∗ such that there is a derivation
S = w0 =⇒r1 w1 =⇒r2 w2 =⇒r3 . . . =⇒rk wk = w,
where k ≥ 1 and, for 1 ≤ i ≤ k, wi−1 = wi−1 Ai wi−1 and wi = wi−1 vi wi−1
for some words wi−1 , wi−1 ∈ (N ∪ T)∗ , ri = (qi , Ai → vi , σi) and, for i < k,
qi+1 ∈ σi.
Excuse the lack of LaTeX.
In a similar way that Ogden's Lemma is stronger than the Pumping Lemma (because of markings), the concept of programmed grammar is stricter than context-free because of these labellings.

Related

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.)

Closure of rational languages under morphism

I have to prove that the set of rational or regular languages is closed by morphism on their alphabet.
i.e. that the image of a rational language by a morphism is still rational.
h being a morphism from Σ to Σ', my idea is to start with an automaton A and to construct an automaton A' which recognizes the language h(L(A)).
I use the same initial and final states then, for any transition (q, a, q') in A, I consider 3 cases :
if h(a) = ε I add the states q, q' (if they do not already exist in A') and an ε transition (q, ε, q')
if h(a) = b ∈ Σ', I add the states q, q' (if they do not already exist in A') and a transition (q, b, q')
if h(a) = b_1b_2...b_n ∈ Σ'*, I add the states q, q' (if they do not already exist in A') plus n-1 new states and n transitions from (q, b_1, q_1) to (q_{n-1}, b_n, q')
Then it's "easy" to prove that h(L(A)) is included in L(A') following the construction steps, however I'm struggling to prove the converse, i.e. that L(A') is included in h(L(A))

Can all context free grammars be converted to NFA/DFA?

I've seen this post about how to convert context free grammar to a DFA:
Automata theory : Conversion of a Context free grammar to a DFA
However, just wondering can all context free grammars be converted to DFA/NFA? What about context free grammars that cannot be expressed as a regular expression? Ex. S->(S) | ()
Thanks!
Only regular languages can be converted to a DFA, and not all CFGs represent regular languages, including the one in the question.
So the answer is "no".
NFAs are not more expressive than DFAs, so the above statement would still be true if you replaced DFA with NFA
A CFG represents a regular language if it is right- or left-linear. But the mere fact that a CFG is not left- or right-linear proves nothing. For example, S→a | a S a happens to generate the same language as S→a | S a a.
Yes ... if the F in "DFA" is replaced by I to get "DIA", but no ... for DFA, itself; and I will show how this works for your example at the end. In fact, all languages have DIA's whose state diagrams reside on a single Universal State Diagram as sub-diagrams thereof.
Consider your example, but rewrite it as S → u S v, S → w. This grammar, like all grammars, is algebraically a system of inequations over a certain partially ordered algebra. In particular, it can be rewritten as
S ⊇ {u}S{v}, S ⊇ {w},
or equivalently as
S ⊇ {u}S{v} ∪ {w}.
The object identified by the grammar is the least solution to the system. Since the system is a fixed point system S ⊇ f(S) = {u}S{v} ∪ {w}, then the least solution may also be described as the least fixed point solution and it is denoted μx f(x) = μx({u}x{v} ∪ {w}).
The ordering relation, for this algebra here, is subset ordering y ⊆ x ⇔ x ⊇ y. The operations include a product AB ≡ { ab: a ∈ A, b ∈ B }, defined element-wise (where, component-wise, the product is word concatenation, with ab being the concatenation of a and b). The product has {1} as an identity, where 1 denotes the empty word. Both word concatenation and product satisfy the fundamental properties
(xy)z = x(yz) [Associativity]
and
xe = x = ex [Identity property]
with the respective identities e = 1 (for concatenation) or e = {1} (for set product). The algebra is called a Monoid.
The simplest and most direct monoid formed from the elements X = {u,v,w} is the Free Monoid X* = {u,v,w}*, which is equivalently described as the set of all words of finite length (including the empty word, 1, of length 0) formed from u, v and w. It is possible to frame the question in terms of more general monoids, but (as the literature usually does) I will restrict it to free monoids.
The family of languages over X is one and the same as the family 𝔓M of subsets A ⊆ M of the monoid M = X*; the defining condition being A ∈ 𝔓M ⇔ A ⊆ M. Other distinguished subfamilies exist, such as the families ℜM ⊆ ℭM ⊆ 𝔗M ⊆ 𝔓M, respectively, of rational, context-free and Turing (or recursively enumerable) languages. The second of these ℭM, which is what your question is concerned with, are given by context-free grammars and are identified as the least fixed point solutions to the corresponding fixed point system of inequations.
Over 𝔓M, one can define the left-quotient operation v\A = { w ∈ M: vw ∈ A }, for each word v ∈ M and subset A ∈ 𝔓M. Because M = X* is a free monoid, it can be decomposed uniquely into left-quotients on the individual elements of X, by the properties 1\A = A, and (vw)\A = w\(v\A).
Correspondingly, one can define a state transition on each x ∈ X by x: A → x\A, treating each subset A ∈ 𝔓M as a state. Together, 𝔓M comprises the state set of the Universal State Diagram over M. Because M = X* is a free monoid, every element of M is either of the form xw for some x ∈ X and w ∈ X*, or is the empty word 1. The decomposition is unique: xw ≠ 1 for any x ∈ X or w ∈ X* and xw = x'w' for x, x' ∈ X and w, w' ∈ X*, only if x = x' and w = w'. Therefore, every A ∈ 𝔓M decomposes uniquely into a partition in a manner analogous to Taylor's Theorem as
A = A₀ ∪ ⋃_{x∈X} {x} x\A.
where A₀ ≡ A ∩ {1} is either {1} if 1 ∈ A or is ∅ if 1 ∉ A. The states for which A₀ = {1} may be regarded as the Final States in the Universal State Diagram.
The analogy to Taylor's Theorem is not too far-removed, since the left-quotient satisfies an analogue of the Product Rule
x\(AB) = (x\A) B ∪ A₀ (x\B)
so it is also denoted as a partial derivative x\A = ∂A/∂x: the Brzozowski Derivative, so that the decomposition rule could just as well be written as:
A = A₀ ∪ ⋃_{x∈X} {x} ∂A/∂x.
What you actually have is an infinite fixed-point system of inequations
A ⊇ A₀ ∪ ⋃_{x∈X} {x} ∂A/∂x for all A ∈ 𝔓M,
with variables A ∈ 𝔓M ranging over all of 𝔓M, whose right-hand sides are all right-linear in the variables. The sets, themselves, are the least fixed point solution to their own system (and to all closed subsystems of the universal system that contain that set as a variable).
Choosing different states as start states yields the different DIA's contained within it. Every minimal DIA (and every minimal DFA) of every language over X is contained in it.
In particular, in this diagram, you can consider the largest subdiagram accessible from a specific state A ∈ 𝔓M. All the states that can be accessed from A are left-quotients by words in M. So, together they comprise a family δA ≡ { v\A: v ∈ M }. The subdiagram consisting only of these states gives you the minimal DIA for the language A, where A, itself, is treated as the start state of the DIA.
If δA is finite, then the I is an F and it's actually a DFA - and that's what you're looking for. Which states in 𝔓M have DIA that are actually DFA's? The regular ones - the ones in the subfamily ℜM ⊆ 𝔓M. This is the case when M = X* is a free monoid. I'm not totally sure if this can also be proven for non-free monoids (like X* × Y*, whose rational subsets ℜ(X* × Y*) are one and the same as what are known as rational transductions) ... because of the reliance on the Taylor's Formula decomposition. There is still something like a Taylor's Theorem, but the decompositions are not necessarily partitions or unique, any longer.
For larger subfamilies of 𝔓M, the DIA are necessarily infinite; but their transitions may possess a sufficient degree of symmetry to allow both the states and transition rules to be wrapped up more succinctly. Correspondingly, one can distinguish different families of DIA by what symmetry properties they possess.
For your example, X = {u,v,w} and M = {u,v,w}*. The subset identified by your grammar is S = {uⁿ w vⁿ: n = 0, 1, 2, ...}. We can define the following sets
S(n) = S {vⁿ}, T(n) = {vⁿ}, for n = 0, 1, 2, ...
The sub-diagram of states accessible from S consists of all the states
δS = { S(n): n = 0, 1, 2, ... } ∪ { T(n): n = 0, 1, 2, ... } ∪ { ∅ }
The state transitions are the following
u: S(n) → S(n+1)
v: T(n+1) → T(n)
w: S(n) → T(n)
with x: A → ∅ in all other cases for x ∈ {u,v,w} and A ∈ δS. The sole final state is T(0).
As you can see, the DIA is infinite and is not a DFA at all. If you were to draw out the diagram, you would see an infinite ladder with S = S(0) being the start state T(0) = {1} the final state, with all the u transitions climbing up a rung, all the v transitions climbing down a rung, and the w transitions crossing over on a rung.
The symmetry is captured by factoring the state set into
δS = {S,T}×{0,1,2,3,⋯} ∪ {∅}
with S(n) rewritten as (S,n) and T(n) as (T,n). This includes a finite set of states Q = {S,T} for a finite state "control" and a set of states D = {0,1,2,3,⋯} for a "device"; as well as the empty set ∅ for the fail state. That device is none other than a counter, and this DIA is just a one-counter automaton in disguise.
All of the classical automata models posed in the literature have a similar form, when expressed as DIA. They contain a state set Q×D ∪ {∅} that includes a finite set Q for the "finite state control" and a (generally infinite) state set D for the device, along with the fail state ∅. The restrictions or constraints on the device correspond to what types of symmetries are contained in the underlying DIA. A deterministic PDA, with two stack symbols {a,b} for instance, has a device state set D = {a,b}* (consisting of all stack words), and an underlying DIA that has the form of an infinite binary tree with copies of Q residing at each node.
You can best see this by writing out and graphing the DIA for the Dyck language, which is given by the grammar D₂ → b D₂ d D₂, D₂ → p D₂ q D₂, D₂ → 1 as a language over X = {b,d,p,q} and subset of M = X* = {b,d,p,q}*; i.e. as the least-fixed point D₂ = μx ({b}x{d}x ∪ {p}x{q}x ∪ {1}).
Every subset in A ⊆ ℭM can be expressed in terms of a subset in A' ⊆ ℜM[b,d,p,q] of the free extension of the monoid M by indeterminates {b,d,p,q}, by carrying out insertions of {b,d,p,q} in suitable places in A, such that the result upon applying the identities {bd} = {1} = {pq}, {bq} = ∅ = {pd}, and xy = yx for x ∈ M and y ∈ {b,d,p,q} will yield A, itself, from A'.
This result (known, but unpublished since the 1990's and published only in 2022) is the algebraic form of the Chomsky-Schützenberger Theorem and is true for all monoids M. For instance, it holds for the non-free monoid M = X* × Y*, where the corresponding family ℭ(X* × Y*) comprise the push-down transductions from X to Y (or "simple syntax directed translations"; aka yacc-like grammars).
So, there is also something like a DFA even for these classes of DIA; provided you include transition arrows for {b,d,p,q}. For your example, A = μx({u}x{v} ∪ {w}), you have A' = {b}{up,qv,w}*{d} and you can easily write down the corresponding DFA. That automaton is just the one-counter machine, itself, with "b" interpreted as "start up at count 0", "d" as "check for count 0 and finish", "p" as "add one to the count" and "q" as "check for count greater than 0 and subtract 1". With respect to the algebraic rules given for {b,d,p,q}, A' is not just a representation of A, it is actually is A: A' = A.

How a^n b^n where n>=1 is not regular?

This is the simple finite automata I tried, what am I doing it wrong?
This matches , not . Aka ababab, not aaabbb.
The b transition leads to a final state which halts the machine. Your machine will only halt if given a sequence of 'ab' of length 1 or more.
The language a^n b^n where n>=1 is not regular, and it can be proved using the pumping lemma. Assume there is a finite state automaton that can accept the language. This finite automaton has a finite number of states k, and there is string x in the language such that n > k. According to the pumping lemma, x can be decomposed such that x=uvw, and any finite automaton that accepts x must also accept uv*w. v is non-empty and can be made to consist of only a's or only b's since n > k. Let v consist of only a's. If the finite automaton accepts x = uvw, it must also accept x = uvvw, which has more a's than b's and is not of the form a^n b^n. This is a contradiction, so a^n b^n cannot be a regular language.
This matches (ab)^n, not a^nb^n.
What you're looking for is Pumping lemma for regular languages.
Examples:
Let L = {a^mb^m | m ≥ 1}.
Then L is not regular.
Proof: Let n be as in Pumping Lemma.
Let w = a^nb^n.
Let w = xyz be as in Pumping Lemma.
Thus, xy^2z ∈ L, however, xy^2z contains more a’s than b’s.

How do I rewrite a context free grammar so that it is LR(1)?

For the given context free grammar:
S -> G $
G -> PG | P
P -> id : R
R -> id R | epsilon
How do I rewrite the grammar so that it is LR(1)?
The current grammar has shift/reduce conflicts when parsing the input "id : .id", where "." is the input pointer for the parser.
This grammar produces the language satisfying the regular expression (id:(id)*)+
It's easy enough to produce an LR(1) grammar for the same language. The trick is finding one which has a similar parse tree, or at least from which the original parse tree can be recovered easily.
Here's a manually generated grammar, which is slightly simplified from the general algorithm. In effect, we rewrite the regular expression:
(id:id*)+
to:
id(:id+)*:id*
which induces the grammar:
S → id G $
G → P G | P'
P' → : R'
P → : R
R' → ε | id R'
R → ε | id R
which is LALR(1).
In effect, we've just shifted all the productions one token to the right, and there is a general algorithm which can be used to create an LR(1) grammar from an LR(k+1) grammar for any k≥1. (The version of this algorithm I'm using comes from Parsing Theory by S. Sippu & E. Soisalon-Soininen, Vol II, section 6.7.)
The non-terminals of the new grammar will have the form (x, V, y) where V is a symbol from the original grammar (either a terminal or a non-terminal) and x and y are terminal sequences of maximum length k such that:
y ∈ FOLLOWk(V)
x ∈ FIRSTk(Vy)
(The lengths of y and consequently x might be less than k if the end of input is included in the follow set. Some people avoid this issue by adding k end symbols, but I think this version is just as simple.)
A non-terminal (x, V, y) will generate the x-derivative of the strings derived from Vy from the original grammar. Informally, the entire grammar is shifted k tokens to the right; each non-terminal matches a string which is missing the first k tokens but is augmented with the following k tokens.
The productions are generated mechanically from the original productions. First, we add a new start symbol, S' with productions:
S' → x (x, S, ε)
for every x ∈ FIRSTk(S). Then, for every production
T → V0 V1 … Vm
we generate the set of productions:
(x0,T,xm+1) → (x0,V0,x1) (x1,V1,x2) … (xm,Vm,xm+1)
and for every terminal A we generate the set of productions
(Ax,A,xB) → B if |x| = k
(Ax,A,x) → ε if |x| ≤ k
Since there is an obvious homomorphism from the productions in the new grammar to the productions in the old grammar, we can directly create the original parse tree, although we need to play some tricks with the semantic values in order to correctly attach them to the parse tree.

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