Sintaxis y Semantica de Lenguajes

UTN – FRM: Sintaxis y Semántica de Lenguajes Diapositiva 1

UTN - FRM: Fundamentos de sintaxis y semántica 1

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Introducción Lenguajes de programación◦ Programas◦ Lenguajes de alto nivel y de máquina◦ Traductores Especificaciones gramaticales y semánticas

Lenguajes formales◦ Alfabeto◦ Palabras

Sintaxis◦ Reglas de formación de palabras

Semántica◦ Significado de las palabras


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Reconocimiento del código fuente de un programa


Texto del programa(caracteres)

Lenguaje de máquina

Léxico

Sintáctico

Semántico

tokens

(palabras)

árboles

(frases)

Análisis

alfabeto

gramática

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Conceptos sobre lenguajes

SímbolosAlfabeto: = {a, b, c, ...}

Cadenas o palabrasn con n >= 0

0 = {} (vacío , , , )

* = 0 1 2 ...

+ = 1 2 ... = * - {}

Universo de un alfabeto W()Todas las palabras formadas con símbolos de

Lenguaje sobre un alfabeto L() W()


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Operaciones con palabrasConcatenación: X.Y

Potencia: Xi

Reflexión: X, X‐1

Operaciones con lenguajesUnión: L1 L2 Intersección: L1 L2

Resta:L1 – L2 Concatenación: L1 L2

Potencia: Li Clausura: L+ = U∞i=1 Li

Cierre: L* = L+ U {} Reflexión: L‐1


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Derivación◦ Regla de producción: x y : x, y *

◦ Derivación directa: v w

◦ Derivación: v v1 v2 … w

◦ Derivación por izquierda y por derecha

◦ Ejemplo:

01 11

00 10

¿Derivaciones para la palabra?

00011

◦ Regla compresora: x y si |y| < |x|


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Gramáticas formales

DefiniciónG = {t, n, S, P}t: conjunto de símbolos terminalesn: conjunto de no-terminales (=t n y t n=)S: axioma : S nP: reglas de producción

Lenguaje generadoL(G) es el conjunto de todas las palabras o cadenas generadas

por la gramática.

EquivalenciaL(G1) = L(G2)


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Gramáticas formales Sea P = { S -> a S b, S -> a S b b, S -> b }

¿ t = ? ¿ n = ? ¿ S = ? ¿Qué genera?


Sea G = ({A}, {a, b, c}, P, S) ¿ conjunto P que genera L1 = {wcw / w E {a, b}*} ?

Sea ∑ = {a, b} y la palabra “aaba” ¿ dos reglas para obtener “aaab” por derecha ?

Sea ∑t = {a, b} ¿ gramática que genera { ar b / r > 0 } ?

Sea ∑t={a,b,c} ¿ gramática que genera { ar b cr/r≥0 } ?

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Jerarquía de ChomskyTipo 0 (sin restricciones) u v

u = x A yu (∑n ∑t)+

v, x, y (∑n ∑t)*

A ∑n

Tipo 1(sensible al contexto)x A y x v y

x, y (∑n ∑t)*

v (∑n ∑t)+

A ∑nS λ (regla compresora)


0

1

2

3

Tipo 2 (independiente del contexto)A v

A ∑nv (∑n ∑t)*

Notación BNF, Pascal

Tipo 3 (regular a dcha. o izq.)A aBA aA λ

A, B ∑na ∑t

Expresiones regulares

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G3 (regulares)

Regular x derechaS 1A

A 1A | 0B | 0

B 0B | 0


Regular x izquierdaS C0

C C0 | D1 | 1

D D1 | 1

Ambas generan11000

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G2 (independientes de contexto)


G1 (no estricta)S AB

A 0A1 | λ

B 2B | λ

G2 (estricta)S AB | A | B | λ

A 0A1 | 01

B 2B | 2

G1 no es estricta ya que incluye reglas nulas asociadas a símbolos que no son el axioma

Ambas generan0n1n2m con n, m ≥ 0

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Árbol de derivación Sea G = { t, n, S, P }t: { 0, 1, [, ], +, * }n: { E }S: EP: { E[EE+], E[EE*], E0, E1 }

Para la cadena: [0[01*]+]


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Árbol de derivación: ambigüedad Sea: S S a S | S b S | c

¿ Qué pasa para cbcac ?

Sea: E E+E | E*E | E^E | id | (E)

◦ Necesidad de reglas de precedencia

* (izq a dcha) + (izq a dcha) ^ (dcha a izq)

E E + E | E E E * E | E

E E ^ E | E E id | (E)

Ejemplo en lenguaje Fortran:

x + algo(3, 4)

¿‘algo’ es un arreglo o una función?


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<assign> <id> := <expr><id> A | B | C<expr> <expr> + <expr>

| <expr> * <expr>| ( <expr> )| <id>

Para ? B := B + A * C (ambigua)

Para ? B := B + ( A * C )

Para ? C := (B + C) * (A := B)


Árbol de derivación: ambigüedad

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Notación BNF y EBNF Es un meta-lenguaje Símbolos no terminales (abstractiones BNF) Símbolos terminales (lexemas)

BNF (John Bakus, Peter Naur Normal Form - 1959)Notación <símbolo> ‘a’ ‘+’ ::= ( ) |Ejemplo <dígito> ::= ‘0’ | ‘1’ | … | ‘9’

<número> ::= <dígito> <número>

<número> ::= <dígito>

EBNF (Extended BNF)Notación { }* o {} { }+ [ ]Ejemplo <dígito> ::= ‘0’ | ‘1’ | … | ‘9’

<número> ::= <dígito> {<dígito>}*


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Diagramas sintácticos


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BNF – EBNF – Diagramas BNF:

<expr> ::= <expr> ‘+’ <term> |

<expr> ‘-’ <term> | <term>

EBNF:<expr> ::= <term> { (‘+’ | ‘-’) <term> }

Diagrama sintáctico


expr term

+

-term

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Notaciones para expresiones


Infija Postfija Prefija

a + d * g - h a d g * + h - - + a * d g h

C

a = a + b

PostScript

/a a b add def

Lisp

(setf a (+ a b))

Infija: operadores entre los operandos

Postfija: operadores posteriores a los operandos

Prefija: operadores anteriores a los operandos

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Autómatas Permiten simular procesos para tratar información◦ la información se codifica en cadenas de símbolos◦ son “dispositivos” que manipulan cadenas de símbolos◦ procesan cadenas de entrada y producen cadenas de salida◦ reciben los símbolos de entrada secuencialmente

El símbolo de salida, en un instante dado depende de◦ el último símbolo de entrada◦ la secuencia o cadena, que ha recibido hasta ese instante◦ el estado en que se encuentra

Estado de un autómata◦ en un instante de tiempo dado, sólo puede estar en un estado◦ estado inicial y estados finales

Formas de descripción: gráfica, matricial, funcional Se usan como reconocedores de lenguajes Existen distintos tipos de autómatas


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Máquina de Mealy

M = (e, s, Q, f, g)e: alfabeto de entrada

s: alfabeto de salida

Q: conjunto de estados f: Q x e Q

g: Q x e s

Transiciones x/y donde◦ x es el símbolo de entrada

◦ y es el símbolo de salida

La salida depende del estado actual y de la entrada


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Máquina de Moore

M = (e, s, Q, f, g)e: alfabeto de entrada

s: alfabeto de salida

Q: conjunto de estados f: Q x e Q

g: Q s

La salida depende sólo del estado actual Para el mismo proceso, suelen tener más estados

que las máquinas de Mealy


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Autómata finito determinista

AFD = (, q0, Q, F, f): alfabeto de entrada q0: estado inicial Q

Q: estados F: estados finales Qf: Q x Q Representaciones


Habitualmente sólo se representan las transiciones que conducen al reconocimiento de alguna cadena, considerándose implícito un "estado

de captación global", donde se supone que llegan los arcos omitidos.

Notación funcionalf(1, a) 2f(1, b) 3f(2, a) 2f(3, b) 2f(3, $) 4f(4, $) 4f(4,2) 3

Notación matricial

a b $ 2

1 2 3 - -

2 2 - - -

3 - 2 4 -

4 - - 4 3

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q0

q1

q2 q3

1

0,10

λ,1

λ

Autómata finito no-determinista

AFND = (, q0, Q, F, f): alfabeto de entrada q0: estado inicial Q

Q: estados F: estados finales Qf: Q x ( {}) P(Q)


1 0 1 0 0 …1

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Gramáticas G3 y autómatas Gramática regular

T = {0, 1}

N = {A, B, S}

P = { S ‐> 0A, A ‐> 0S, A ‐> 1B, B ‐> 1, B ‐> 0 }

Autómata

Expresión regular0.(0.0)*.1.(1|0)


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Introducidas en 1956 por Kleene◦ Describen AEF

Operadores

Unión | V +

Concatenación .

Cierre (Kleene) *

Cierre (positivo) +

Sea a.(b|c*).d ¿cuál es el AEF y la gramática?


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Propiedades de las ER


Sea L = {a, b, c}*¿ Son equivalentes: c*.c | c* = c* ?

1)

2)

3)

4)

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Expresiones regulares y AEF


qi qk qfa ba.bqi qf

a

ba|b

qi qk qf

E E

a

a*

Se pueden transformar aplicando reglas de la forma:

Existen algoritmos formales◦ Algoritmo de McNaughton-Yamada-Thompson

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Algoritmo de transformación


Por ejemplo sea (1 | 0)*1 se obtiene un AFND

luego se lo convierte a

un AFD

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Equivalencia de autómatas


AFND AFD Un AFD es un caso particular de AFND Sean N=(∑, q0, Q, F, f) y D=(∑, {q’0}, Q’, F’, f ’)

◦ N = D / L(D)=L(N)◦ Si se cumple: Q’ = 2|Q| (conjunto potencia P(Q) ) q’i = [qi , …, qf ] => {qi , …, qf} Q’

q’0 = {q0} F’ = { q’ Q’ / q’ ∩ F ≠ } (al menos uno sea final)

f ’(q’, a) = { qq’ f(q, a)} / q Q ^ a ∑

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Equivalencia de autómatas Se basa en la construcción de subconjuntos La idea general es que cada estado del AFD

le corresponde un conjunto de estados del AFND

Algoritmo:◦ Para cada estado del AFND y cada símbolo de

entrada, analizar cuáles estados son alcanzables◦ Agrupar esos estados en estados compuestos◦ Hacer lo mismo con los estados compuestos◦ Finalmente, eliminar los estados que no son

alcanzables (menos inicial y final)


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Equivalencia de autómatas

AFND

AFD: estados alcanzables desde {q0}


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Minimización de autómatas


Sean AFD=(∑, q0, Q, F, f) =AFDM=(∑, q’0, Q’, F’, f ’) / L(AFD)=L(AFDM)a) Eliminar los estados no alcanzables desde el estado inicialb) Eliminar los estados desde los que no se alcanza un estado finalAlgoritmo:

1. partición inicial P en dos grupos G’(F), G’’(Q – F)2. G de P (|G| > 1) obtener nueva Pn de modo que:

1. qi, qj Gi <=> ∑ / f(qi, ), f(qj, ) Gi

2. sustituir G en Pn por el nuevo conjunto de subgrupos3. si Pn= P (indistinguibles) entonces Pfinal := P e ir a (5)4. sino P := Pn e ir a (2)5. elegir en cada grupo de Pfinal, un qi como representante del

grupo6. se eliminan estados pasivos (que no son finales y hay transiciones

hacia ellos, pero no desde ellos hacia otros estados)

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Minimización de autómatas

Sea el AFD que reconoce L = (a|b)*abb

Minimización:1. P := G1{Q5} + G2{Q1,Q2,Q3,Q4}

2. Pn := {Q5} y (Q1, Q2, Q3) x b G2 y Q4 x b G1

3. Pn := G1{Q5} + G2{Q1, Q2, Q3} + G3{Q4}

4. si Pn ≠ P entonces P := Pn y repite

5. Pn := {Q5} + {Q4} y {Q1, Q3} x b G2 y Q2 x b G3

6. Pn := G1{Q5} + G2{Q4} + G3{Q1, Q3} + G4{Q2}

7. como Pn ≠ P entonces P := Pn y repite

pero se obtiene la misma P

1. luego Pn = P entonces

Pfinal := P

1. Q1 representa a G3


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Conceptos


Lenguajes regulares

Gramáticas regulares (G3)


Autómatas de estado finito

Lema del bombeoSi Lr∞ => xyz є L / y ≠ λ, xynz є L para n > 0

Exp. Reg. Y AEF

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Casos AEFND AEFD

Minimizar


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Autómatas de pila


Autómata de PilaAP = ( Σ, , Q, a0, q0, F, f ) Σ: alfabeto de entrada: alfabeto de pila q0: estado inicialQ: conjunto de estados F: estados finalesa0: símbolo inicial pila f: Q ({ε}) Q

Controlpila

cinta

Para cada gramática G independiente del contexto, existe un autómata de pila M tal que L(G)=L(M)

Los símbolos en la pila se ordenan en sentido cima base (convención)

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Gramáticas G2 y AP


Descripción instantánea: terna (q, h / w) donde: q = estado actualh = símbolo leído de la cima de la pilaw = símbolo escrito en la pila

Gramática libre de contexto

T = {a, b} N = {S}

P = { S -> aSb| λ }

L1 = {anbn / n >= 0}

Autómata de Pila

Σ: {a, b} q0: e0

: {#, $} F: {e3}

Q: {e0,e1,e2,e3} a0:

q0 q2q1 q3,

a, a

b, a

b, a

, $ $

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Autómatas de pila Descripción funcional

f: e0 x ε x ε e1 x $e1 x ε x ε e2 x εe1 x 0 x ε e1 x #e2 x ε x $ e3 x εe2 x 1 x # e2 x ε

Descripción tabular


Estado Entrada Pila Transición

e0 ε ε e1,$

e1 ε ε e2,ε

e1 0 ε e1,#

e2 ε $ e3,ε

e2 1 # e2,ε

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Autómatas de pila

Reconocimiento por vaciado de pilaLvp(M)= {w Σ* / (q0, w, a0) (p, ε, ε), p Q}

Reconocimiento por estado finalLef(M)={w Σ*/ (q0, w, a0) (p, ε, h), p F, h *}

Lvp puede ser diferente de Lef


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Autómatas de pila Es determinista si cumple

(q Q A Γ ) si |f(q, ε, A)|>0 a Σ, f(q, a, A)=(q Q A Γ a Σ {ε} ), |f(q, a, A)|<2

Construcción de un AP (Σ, Γ, Q, a0, q0, f, F)

◦ Dados: ∑={a, b, c}, ={#, $, ε }, a0 = #, q0=X, Q={X, Y, Z}, F= {Z}

◦ ¿ f ? para reconocer: L = { an b cn+1 / n > 0 }

AP <=> G2


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Autómatas de pila y gramáticas

Representar G2 con AP◦ AP ( Σ, , Q, a0, q0, F, f ) entonces construir

APND=(Σ, Σ N, {q}, S, q, fi, f) sea A→w P entonces (q, w) f(q, ε, A) sea a Σ entonces (q, ε) f(q, a, a)◦ El reconocimiento es por vaciado de pila◦ Sea P = { S→0S1, S→c } entonces f(q, ε, A)= {(q, 0S1), (q, c)}

f(q, 0, 0)= f(q,1,1)= f(q, c, c)= {(q, ε)}


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Algoritmo para convertir G2 en AP


Dada una gramática G independiente del contexto, se construye un autómata de pila M de la siguiente forma:

1. Designar el alfabeto de M como los símbolos terminales de G; y los símbolos de pila de M como los símbolos terminales y no terminales de G, junto con # (si # no es un símbolo terminal o no terminal a G)

2. Designar los estados de M como i, p, q y fi; donde i es el estado inicial y fi es el único estado de aceptación

3. Agregar la transición (i, ,; p, #)

4. Agregar una transición (p, ,; q, S) donde S es el símbolo inicial de G

5. Agregar una transición de la forma (q, ,N; q,w) para cada regla de reescritura Nw en G, donde w puede ser una cadena de cero o mas símbolos, incluyendo terminales y no terminales

6. Agregar una transición de la forma (q, x, x; q, ) para cada terminal x de G (para cada símbolo del alfabeto de M)

7. Agregar la transición (q, , #; fi, )

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Algoritmo para convertir G2 en AP

SzMNzMaMaMzNbNbNz


Σ = {a, b, z} = {a, b, z, S, M, N, #}Q = {i, p, q, fi}a0 = #q0 = iF = fi

G2: AP:

Comportamiento

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Autómata Linealmente AcotadoALA= (Q, ∑, , , e0, b, F) donde b = blanco

longitudcinta = longitudcadena

Q: conjunto finito estados∑ : alfabeto de entrada; ∑ (input) : ∑ {b} otros símbolos, b ∑ (output)

: Q x Q x x {D, I, N}e0: estado inicial QF: estados finales Q


cinta

Controlestados

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Máquinas de TuringAP = (, Σ, b, Q, q0, F, f)Σ: alfabeto de entrada Σc: alfabeto de la cintab: blanco Σc, ΣeQ: conjunto de estadosq0: estado inicial QF: estados finales Qf: Q x Σc Q x Σc x {I, D, P}


cinta

Controlestados

… …

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Máquinas de Turing

Los movimientos se repiten hasta que:◦ llega al estado final (se detiene aceptando la entrada)◦ intenta acceder a la celda a la izquierda de la celda

inicial (se detiene rechazando la entrada)◦ entra en una situación para la que no hay definido

movimiento (se detiene rechazando la entrada)◦ ante determinada entrada, la máquina siga realizando

movimientos indefinidamente sin aceptar ni rechazar dicha entrada

Palabra y lenguaje aceptado◦ x L(M) q0x 1q2 : 1,2 , q F◦ L(M) = { x * | q0x 1q2 : 1,2 , q F }


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Máquinas de Turing

Máquina que acepta el lenguaje de palabras sobre {0, 1} que comienzan y terminan con el mismo símbolo


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Máquinas de Turing


0q 1q 2q

3q

R,1$

L,1

L,

R$,1 L,11 R,11

R,

Concatenador

Duplicador

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Gramáticas y autómatas


3: lenguajes regulares

autómatas finitos

2: lenguajes independientes del contexto autómatas de pila1: lenguajes sensibles al contexto

autómatas linealmente acotados

0: lenguajes irrestrictos máquinas de Turing

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Análisis léxico Scanner◦ agrupar caracteres de entrada en tokens◦ detectar algunos significados y errores a veces debe realizar una doble función: identificar el token y

“evaluar” el token

◦ introducir información adicional algunos tokens requieren algo más que su propia identificación constantes: su valor, identificadores: el string, etc.

◦ eliminar separadores innecesarios ◦ sustituir macros


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Análisis léxico


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Análisis léxico


lexema

• secuencia de caracteres, que se asocia a un token

token

• nombre de cada componente léxico

patrón

• conjunto de lexemas

Enunciado

index = 2 * count + 17

Lexemasindex=2*count+17;

Tokensidentifierequal_signint_literalmult_opidentifierplus_opint_literalsemicolon

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Análisis sintáctico Parser◦ agrupar los tokens suministrados por el scanner

para reconocer frases determinar si son sintácticamente correctas establecer la estructura subyacente

◦ recibir tokens y agruparlos de acuerdo a producciones especificadas por la G3◦ detectar errores sintácticos◦ generar árboles sintácticos


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Análisis sintáctico


Proceso de análisis

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Árboles de sintaxis◦ Concreta: sirve para el análisis sintáctico◦ Abstracta: sirve para el análisis semántico

Sea: S if expr then A endif ;

Concreta Abstracta (AST)

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Análisis sintáctico Analizadores recursivos cada no-terminal tiene asociada una rutina de análisis,

creada a partir de las reglas gramaticales scan de izquierda a derecha

Estrategias de análisis◦ DESCENDENTE(Top-Down) construye el árbol desde la raíz (S) hacia las hojas problemas con recursividad a izquierda

◦ ASCENDENTE(Bottom-Up) construye el árbol desde las hojas hacia la raíz (S) se basa en encontrar una derivación por la derecha


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Analizador por izquierda (a)


Sea la gramática G = (N, T, S, P) con◦ N = {A, S}, T = {a, b, c},◦ P = {S → aAc, A →Ab | λ }◦ L = {a bn c / n > 0}.

Se quiere reconocer: abbc

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Analizador por izquierda (b)


Sea la gramática G = (N, T, S, P) con◦ N = {A, S}, T = {a, b, c},◦ P = {S → aAc, A → λ | Ab}◦ L = {a bn c / n>=0}.

Se quiere reconocer: abbc

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Recursividad a izquierda

Analizador top-down no puede procesarla RI Inmediata

A A |

Para eliminarla◦ Se trabaja con el término (que no es RI)

A BB B |


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Eliminación recursividad izq. Sea

S Aa | b

A Ac | Sd | f

◦ Reemplazar: A Sd por A Aad | bd

◦ Queda: A Ac | Aad | bd | f

◦ Eliminar recursividad inmediata:

A bdA’ | fA’

A’ cA’ | adA’ | ◦ Finalmente:

S Aa | b

A bdA’ | fA’

A’ cA’ | adA’ |


Resolver:S a B | cB B a | c

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Analizador descendente Problema del retroceso, sea: G = (N, T, S, P)N = {<PROGRAMA>, <DECLARACIONES>, <PROCEDIMIENTOS> }

T = {module, d, p, ;, end}

S = <PROGRAMA>

P = {

<PROGRAMA> ::= module <DECLARACIONES>; <PROCEDIMIENTOS> end

<DECLARACIONES> ::= d | d; <DECLARACIONES>

<PROCEDIMIENTOS> ::= p | p; <PROCEDIMIENTOS> }

Analizar aplicando derivaciones Leftmost module d ; d ; p ; p end


_

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Análisis sintáctico Gramáticas LL(k) y analizadores◦ subconjunto de las gramáticas libres de contexto◦ permiten un análisis descendente sin retroceso◦ L = reconocimiento de la cadena de entrada de

izquierda a derecha ◦ L = toman las derivaciones más hacia la izquierda

("Leftmost") con sólo mirar los k tokens situados a continuación de donde se halla si k=1 se habla de gramáticas LL(1)◦ permiten construir un analizador determinista

descendente sólo examinan en cada momento el símbolo actual de la

cadena de entrada para saber que producción aplicar


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Gramáticas LR(k) y analizadores◦ Analizadores LR L = lee entrada de izquierda a derecha (Left-to-right) R = analiza aplicando derivaciones más a la derecha

en sentido inverso (Rightmost) k = número de símbolos de entrada por delante

(lookaheads) que lee el analizador (gramática LR(k)) eficiente análisis ascendente sin retroceso detectan errores sintácticos rápidamente pueden construirse para la mayoría de las G2 complicados de construir


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Analizador ascendente Sean◦ Producción: E→E+E | E*E | (E) | -E | id◦ Enunciado: id+id*id◦ Derivaciones:


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Analizador ascendente

Esquema del algoritmo


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Analizador ascendente


Pila Árbol Entrada Regla

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análisis léxico


sup = alto*ancho;

Fases de análisis

(id,sup)(asignador)(id,alto)(opMult)(id,ancho)(separador)

análisis sintáctico

análisis semántico

(asignador)

(id,sup) (opMult)

(id,alto) (id,ancho)

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Semántica La sintaxis no es suficiente para describir un

lenguaje. La semántica:◦ Define “qué hacen” los enunciados de un lenguaje.◦ Posibilita implementar correctamente el lenguaje.◦ Sirve para desarrollar técnicas y herramientas de: Análisis y Optimización Depuración Verificación Transformación

◦ Ayuda a “razonar sobre el funcionamiento” de un programa (recursos usados, corrección, …)


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Semántica estática Se calcula en tiempo de compilación◦ Tipología de datos De la signatura de funciones Accesos a variables deben coincidir con su declaración Identificadores y expresiones deben ser evaluables Left-side debe ser asignable Expresiones, funciones y operadores compatibles

◦ Flujo de control Accesibilidad de las variables para su uso

◦ Unicidad Uso de identificadores únicos

Ejemplovar A: integer; Significado almacenamiento para A


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Semántica dinámica Ciertos significados se pueden detectar durante

la ejecución◦ Punteros con referencias nulas◦ Valores límites de subíndices de arreglos◦ Consistencia en el pasaje de argumentos◦ Otros: x := z / y ¿si y == 0?

Otros no es posible◦ Errores de “lógica” cambian la semántica de un

enunciado, pero no son estrictamente, errores semánticos de los enunciadosx := z / y si lo que se quería escribir era x := z * y

Ejemplos = “hola”; s = 45.78; “25” + 5 “255”


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Especificación de la semántica La especificación sintáctica, en notación BNF es prácticamente

universal, en tanto que para la semántica, existen diversas técnicas sin que ninguna sea universal.

Es deseable satisfacer características tales como:◦ No ambigüedad: facilitar la creación de descripciones rigurosas.◦ Demostración: permitir la posterior demostración de propiedades de

los programas escritos en el lenguaje especificado.◦ Prototipado: posibilitar obtener prototipos ejecutables de los lenguajes

que se diseñan de forma automática.◦ Modularidad: realizar la especificación de forma incremental.◦ Reusabilidad: facilitar la reutilización de descripciones en diferentes

lenguajes.◦ Legibilidad: ser legibles por personas con formaciones heterogénea. ◦ Flexibilidad: adaptarse a la variedad de lenguajes existentes.◦ Experiencia: ser capaz de describir lenguajes reales, no sólo sencillos o

experimentales.


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Metodologías para especificar Lenguaje Natural: con restricciones. Operacional: se especifican las transiciones elementales

de un programa mediante reglas de inferencia definidas por inducción sobre su estructura.

Denotacional: se describe modelando los significados mediante entidades matemáticas básicas.

Axiomática: se definen una serie de reglas de inferencia que caracterizan las propiedades de las diferentes construcciones del lenguaje.

Algebraica: permite definir una estructura matemática de forma abstracta junto con las propiedades que debe cumplir.


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Metodologías para especificar


Máquina de Estado Abstracto: se definen algoritmos mediante una abstracción del estado sobre el que se trabaja y una serie de reglas de transición entre elementos de dicho estado.

Semántica de Acción: se definen acciones, que expresan computaciones.

Monádica Modular: se definen mónadas y transformadores de ellas (una mónada separa una computación del valor devuelto por la misma).

Monádica Reutilizable: añade conceptos de programación genérica a la anterior.

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Resumen de características


NAM MOD REU DEM PRO LEG FLE EXP

Nat. S S Reg S S

Oper. S Reg Reg Reg S S

Deno. S S Reg S Reg

Axio. Reg S Reg S

Alge. S Reg S S Reg Reg R

Estad. S S Reg Reg S Reg S

Acc. S S Reg Reg S Reg Reg

Modu. S S S Reg S

Reuti. S S S S S S

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Implementación de la semántica


Hardware

Lenguaje de máquina

Lenguaje ensamblador o pseudolenguajes

Implementación de la semántica

Atr

ibut

os

Ope

raci

onal

Den

otat

iva

Axi

omát

ica

...

Nat

uralEspecificaciones

semánticas

Estructuras de datos + algoritmos

Construircompilador(traductor)

Construirenlazador o intérprete

Intérprete en hardware

C, C++, Java, Ruby, JS, PHP, Ada, Pascal, Cobol, Fortran, …

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Sintaxis y Semantica de Lenguajes

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Transcript of Sintaxis y Semantica de Lenguajes