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El error de la regla de entrada: socio OR (invitado AND NOT vetado) y el caso que difiere

La regla prevista (member OR invited) AND NOT banned comparada con el error member OR (invited AND NOT banned). La comprobación de equivalencia falla, y la tabla de verdad señala las dos filas en las que el error deja entrar a una persona vetada.

Las dos fórmulas usan las mismas tres entradas: member, invited y banned. La regla prevista aplica el veto a todo el mundo: seas quien seas, banned = VERDADERO te deja fuera. El error mueve los paréntesis de modo que el veto solo afecta a los invitados; a un socio lo deja pasar el primer disyunto antes de mirar siquiera el veto. Dichas en voz alta las dos reglas suenan casi igual, y por eso el error sobrevive a la revisión de código. En la tabla de ocho filas no se parecen en nada.

La comprobación de equivalencia se viola e informa del contraejemplo member = VERDADERO, invited = FALSO, banned = VERDADERO: la regla prevista dice no, el error dice sí. La tabla marca dos filas que difieren, la 5 y la 7, member = VERDADERO, invited = FALSO, banned = VERDADERO y member = VERDADERO, invited = VERDADERO, banned = VERDADERO; en las otras seis coinciden. La regla prevista es verdadera en tres filas, Σm(2, 4, 6); el error en cinco. Las comprobaciones sobre la regla prevista son las de su página: ni tautología ni contradicción, satisfacible con el testigo member = FALSO, invited = VERDADERO, banned = FALSO.

Todas las filas que difieren tienen banned = VERDADERO y member = VERDADERO, así que el error no es un fallo cualquiera: es exactamente un socio vetado que entra. Este es el patrón que hay que buscar siempre que una regla tenga un OR de permisos y un AND con una exclusión. Una batería de pruebas que solo ensaya socios normales, invitados normales y desconocidos aprueba las dos versiones; las dos filas que encontró el comprobador son las pruebas que faltaban. Anótalas, y deja la comprobación de equivalencia en la cadena de integración para que una refactorización posterior no reintroduzca el error.

intended := (member OR invited) AND NOT banned · salidaslip := member OR (invited AND NOT banned) · salida

Comprobaciones exactas

¿Siempre verdadera (tautología)? No Contraejemplo: member = F, invited = F, banned = F · Exhaustively checked and solver cross-checked · 1 filas
¿Siempre falsa (contradicción)? No Contraejemplo: member = F, invited = V, banned = F · Exhaustively checked and solver cross-checked · 3 filas
¿Puede ser verdadera? Sí Asignación de ejemplo: member = F, invited = V, banned = F · Exhaustively checked and solver cross-checked · 3 filas
¿Son equivalentes intended y slip? No Contraejemplo: member = V, invited = F, banned = V · Exhaustively checked and solver cross-checked · 6 filas

Tabla de verdad (8 filas)

El error de la regla de entrada: socio OR (invitado AND NOT vetado) y el caso que difiere
#memberinvitedbannedintendedslip
0FALSOFALSOFALSOFALSOFALSO
1FALSOFALSOVERDADEROFALSOFALSO
2FALSOVERDADEROFALSOVERDADEROVERDADERO
3FALSOVERDADEROVERDADEROFALSOFALSO
4VERDADEROFALSOFALSOVERDADEROVERDADERO
5VERDADEROFALSOVERDADEROFALSOVERDADERO
6VERDADEROVERDADEROFALSOVERDADEROVERDADERO
7VERDADEROVERDADEROVERDADEROFALSOVERDADERO

Lectura en lenguaje claro

Principianteintended es verdadero exactamente cuando se cumplen las dos condiciones siguientes:
1. al menos uno entre member e invited es verdadero (pueden serlo ambos)
2. banned es falso
En todos los demás casos, intended es falso.
Sobre los operadores:
- AND (Y) solo es verdadero cuando todas sus partes son verdaderas.
- OR (O) es inclusivo: es verdadero en cuanto al menos una parte es verdadera, también cuando lo son varias.
- NOT (NO) invierte un valor: lo verdadero pasa a ser falso y lo falso, verdadero.
Intermediointended es verdadero exactamente cuando se cumplen las dos condiciones siguientes:
1. al menos uno entre member e invited es verdadero (pueden serlo ambos)
2. banned es falso
En todos los demás casos, intended es falso.
Avanzadointended es verdadero exactamente cuando se cumplen las dos condiciones siguientes [conjunción ∧]:
1. al menos uno entre member e invited es verdadero (pueden serlo ambos) [disyunción inclusiva ∨]
2. banned es falso [negación ¬]
En todos los demás casos, intended es falso.
Notación formal: (member ∨ invited) ∧ ¬banned

Diagrama lógico

Entry rule slip: member OR (invited AND NOT banned) and the case that differs Entry rule slip: member OR (invited AND NOT banned) and the case that differs member invited banned intendedPRIMARY slip AND OR NOT OR AND NOT
Entry rule slip: member OR (invited AND NOT banned) and the case that differs Entry rule slip: member OR (invited AND NOT banned) and the case that differs member invited banned intendedPRIMARY slip AND OR NOT OR AND NOT

Simplificación paso a paso

El motor no encontró ninguna ley que acorte esta expresión; ya es tan corta como sus leyes de reescritura permiten.

(member OR invited) AND NOT banned

Mapa de Karnaugh

member \ invitedbanned
00
01
11
10
0
0m0
0m1
0m3
1m2
1
1m4
0m5
0m7
1m6
  1. celdas m4, m6member AND NOT banned
  2. celdas m2, m6invited AND NOT banned
(member AND NOT banned) OR (invited AND NOT banned) · Derived (member AND NOT banned) OR (invited AND NOT banned). Exactly equivalent on every assignment.

Mintérminos y maxtérminos

intended(member, invited, banned) = Σm(2, 4, 6)intended(member, invited, banned) = ΠM(0, 1, 3, 5, 7)

Orden de variables: member, invited, banned · 8 filas

Formas normales

Forma normal conjuntiva (FNC)

(member OR invited) AND NOT banned

2 cláusulas, 3 literales · complete

Forma normal disyuntiva (FND)

(member AND NOT banned) OR (invited AND NOT banned)

2 términos, 4 literales · complete · Distributividad ×1

Solo NAND, solo NOR

Forma solo con NAND

NAND(NAND(NAND(NAND(member, member), NAND(invited, invited)), NAND(banned, banned)), NAND(NAND(NAND(member, member), NAND(invited, invited)), NAND(banned, banned)))

11 compuertas · equivalencia verificada en todas las filas

Forma solo con NOR

NOR(NOR(member, invited), banned)

2 compuertas · equivalencia verificada en todas las filas

La misma regla como código

Python
# -*- coding: utf-8 -*-
# Generated by Tangibool (tangibool.python/1). Do not edit by hand; regenerate from the source revision.
# Model: not stated
# Source revision: reference
# Interpretation status: not stated
"""Tangibool evaluator (decision model).

Generated deterministically from the validated Boolean model; it evaluates exactly that
model. It does not establish that the model is a complete, legal, or safe statement of a
real-world rule, and evaluating examples does not verify the rule.

Source revision: reference
Interpretation status: not stated
Exporter: 1.0.0 (format tangibool.python/1; engine 1.0.0; semantics tangibool-semantics/1)
Logic digest: 91a23ad742858028ac5d50195304c533a2ef7b50d25f63acb5fb8f991c557419
Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78

Inputs (dict keys, declared order) and generated parameter names:
    'member' -> input_member
    'invited' -> input_invited
    'banned' -> input_banned

Outputs (declared order) and their functions:
    'intended' -> output_intended(inputs)
    'slip' -> output_slip(inputs)

Assumptions (the declared scope, checked by in_scope(inputs)):
    none; every complete assignment is in scope.

Input contract:
    Every required input must be exactly True or False (type(value) is bool). Missing
    inputs, None, strings, integers (including 0 and 1), and keys that are not declared
    inputs raise InputError before anything is evaluated, including inputs that a
    short-circuiting operator would never read. Results are always bool.

Scope:
    Decision functions raise OutOfScopeError when the inputs violate an assumption; an
    out-of-scope assignment is never turned into a False result. Pass check_scope=False
    to evaluate without the scope check, and use in_scope(inputs) to test it separately.

Usage:

    import tangibool_model as model

    model.evaluate({'member': False, 'invited': False, 'banned': False})
    # -> {'intended': False, 'slip': False}
    model.output_intended({'member': False, 'invited': False, 'banned': False})
    # -> False
    model.evaluate({'member': 1, 'invited': False, 'banned': False})
    # raises InputError: 1 is an int, not a bool
"""

import collections.abc as _abc
from typing import Dict, Mapping, Tuple

__all__ = [
    "MODEL_INFO",
    "IDENTIFIER_MAP",
    "INPUT_NAMES",
    "OUTPUT_NAMES",
    "ASSUMPTIONS",
    "InputError",
    "OutOfScopeError",
    "minterm_index",
    "in_scope",
    "evaluate",
    "output_intended",
    "output_slip",
]

MODEL_INFO = {
    "format": "tangibool.python/1",
    "mode": "decision",
    "model": None,
    "revision": "reference",
    "interpretation": None,
    "exporter": "1.0.0",
    "engine_version": "1.0.0",
    "semantics_version": "tangibool-semantics/1",
    "logic_digest": "91a23ad742858028ac5d50195304c533a2ef7b50d25f63acb5fb8f991c557419",
    "assumptions_digest": "d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78",
    "primary_output": "intended",
    "unused_inputs": (),
    "subcircuits": (),
}

# Stable ID -> generated identifier (reversible mapping; names are exact, escaped strings).
IDENTIFIER_MAP = {
    "v_0fc060df0343": {"kind": "input", "name": "member", "identifier": "input_member"},
    "v_f56b70a5523e": {"kind": "input", "name": "invited", "identifier": "input_invited"},
    "v_8d70674fa3c9": {"kind": "input", "name": "banned", "identifier": "input_banned"},
    "f_c04b24230e13": {"kind": "output", "name": "intended", "identifier": "output_intended"},
    "f_e966114fcb43": {"kind": "output", "name": "slip", "identifier": "output_slip"},
}

INPUT_NAMES = ("member", "invited", "banned")
OUTPUT_NAMES = ("intended", "slip")
ASSUMPTIONS = ()

_DECLARED_INPUTS = frozenset(INPUT_NAMES)
_SCOPE_INPUTS = ()
_ASSUMPTION_FORMULAS = {entry["name"]: entry["formula"] for entry in ASSUMPTIONS}


class InputError(ValueError):
    """Raised when inputs are missing, undeclared, or not exactly True/False.

    Every required input must satisfy type(value) is bool. Missing inputs, None, strings,
    integers (including 0 and 1), and keys that are not declared inputs are rejected before
    anything is evaluated. A missing input is never treated as False. The individual problems
    are listed in the problems attribute.
    """

    def __init__(self, problems):
        self.problems = tuple(problems)
        super().__init__("Invalid inputs: " + "; ".join(self.problems))


class OutOfScopeError(ValueError):
    """Raised when the inputs violate the model's assumptions (its declared scope).

    Outside its assumptions the rule has no decision: this error is never a False result.
    The names of the violated assumptions are in the violated attribute.
    """

    def __init__(self, violated):
        self.violated = tuple(violated)
        details = ", ".join(name + " (" + _ASSUMPTION_FORMULAS.get(name, "?") + ")" for name in self.violated)
        super().__init__(
            "Out of scope: the inputs violate "
            + ("assumption " if len(self.violated) == 1 else "assumptions ")
            + details
            + ". The rule has no decision outside its assumptions; this is not a False result."
        )


def _short_repr(value: object) -> str:
    text = repr(value)
    return text if len(text) <= 60 else text[:57] + "..."


def _checked_inputs(inputs: Mapping[str, bool], required: Tuple[str, ...], check_scope: bool) -> Dict[str, bool]:
    """Validate inputs strictly before anything is evaluated and return a plain copy."""
    if type(check_scope) is not bool:
        raise TypeError("check_scope must be True or False")
    if not isinstance(inputs, _abc.Mapping):
        raise InputError(["inputs must be a mapping from input names to True/False, got " + type(inputs).__name__])
    problems = []
    for key in inputs:
        if type(key) is not str or key not in _DECLARED_INPUTS:
            declared = ", ".join(repr(name) for name in INPUT_NAMES) or "none"
            problems.append("undeclared input " + _short_repr(key) + " (declared inputs: " + declared + ")")
    needed = tuple(required) + (_SCOPE_INPUTS if check_scope else ())
    for name in needed:
        if name not in inputs:
            problems.append("missing required input " + repr(name))
    for key, value in inputs.items():
        if type(key) is str and key in _DECLARED_INPUTS and type(value) is not bool:
            problems.append(
                "input " + repr(key) + " must be True or False (type bool), got "
                + type(value).__name__ + " " + _short_repr(value)
            )
    if problems:
        raise InputError(list(dict.fromkeys(problems)))
    return dict(inputs.items())


def _require_bool_args(function: str, pairs: Tuple[Tuple[str, object], ...]) -> None:
    problems = [
        "argument " + repr(name) + " of " + function + " must be True or False (type bool), got "
        + type(value).__name__ + " " + _short_repr(value)
        for name, value in pairs
        if type(value) is not bool
    ]
    if problems:
        raise InputError(problems)


def minterm_index(*values: bool) -> int:
    """Row index of an assignment over a declared variable order.

    The first value is the most significant bit, so all-False is row 0. Used for indexed
    minterm (sum) and maxterm (product) forms.
    """
    index = 0
    for value in values:
        if type(value) is not bool:
            raise InputError(["minterm_index() takes True/False values, got " + type(value).__name__ + " " + _short_repr(value)])
        index = index * 2 + (1 if value else 0)
    return index


def _scope_values(values: Dict[str, bool]) -> Tuple[Tuple[str, bool], ...]:
    """Value of every enabled, confirmed assumption for validated inputs, in declared order."""
    return ()


def _require_in_scope(values: Dict[str, bool]) -> None:
    violated = tuple(name for name, holds in _scope_values(values) if not holds)
    if violated:
        raise OutOfScopeError(violated)


def in_scope(inputs: Mapping[str, bool]) -> bool:
    """True when the inputs satisfy every assumption (the model's declared scope).

    Requires the inputs the assumptions read; raises InputError for invalid inputs.
    """
    values = _checked_inputs(inputs, (), True)
    return all(holds for _, holds in _scope_values(values))


# ---- Formula bodies (inputs are validated by the public functions below) ----


def _compute_output_intended(input_member: bool, input_invited: bool, input_banned: bool) -> bool:
    """Decision output 'intended': (member OR invited) AND NOT banned"""
    return (input_member or input_invited) and (not input_banned)


def _compute_output_slip(input_member: bool, input_invited: bool, input_banned: bool) -> bool:
    """Decision output 'slip': member OR (invited AND NOT banned)"""
    return input_member or (input_invited and (not input_banned))


# ---- Public API ----


def output_intended(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'intended' (stable ID f_c04b24230e13).

    'intended' := (member OR invited) AND NOT banned

    Required inputs: 'member', 'invited', 'banned'.
    Raises InputError for missing, undeclared, or non-bool inputs, and OutOfScopeError
    when check_scope is True and the inputs violate an assumption.
    """
    values = _checked_inputs(inputs, ("member", "invited", "banned"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_intended_value = _compute_output_intended(values["member"], values["invited"], values["banned"])
    return output_intended_value


def output_slip(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'slip' (stable ID f_e966114fcb43).

    'slip' := member OR (invited AND NOT banned)

    Required inputs: 'member', 'invited', 'banned'.
    Raises InputError for missing, undeclared, or non-bool inputs, and OutOfScopeError
    when check_scope is True and the inputs violate an assumption.
    """
    values = _checked_inputs(inputs, ("member", "invited", "banned"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_slip_value = _compute_output_slip(values["member"], values["invited"], values["banned"])
    return output_slip_value


def evaluate(inputs: Mapping[str, bool], *, check_scope: bool = True) -> Dict[str, bool]:
    """Evaluate every output (declared order); each output is computed once.

    Required inputs: 'member', 'invited', 'banned'.
    Raises InputError for missing, undeclared, or non-bool inputs, and OutOfScopeError
    when check_scope is True and the inputs violate an assumption.
    """
    values = _checked_inputs(inputs, ("member", "invited", "banned"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_intended_value = _compute_output_intended(values["member"], values["invited"], values["banned"])
    output_slip_value = _compute_output_slip(values["member"], values["invited"], values["banned"])
    return {
        "intended": output_intended_value,
        "slip": output_slip_value,
    }
PostgreSQL
-- Tangibool PostgreSQL export (tangibool.postgresql/1)
-- Target: PostgreSQL 16 or later with typed boolean inputs; tested with PostgreSQL 18.3 (PGlite 0.5.8).
-- Not a claim of compatibility with other SQL dialects.
-- Model: not stated
-- Source revision: reference
-- Interpretation status: not stated
-- Exporter: 1.0.0 (engine 1.0.0; semantics tangibool-semantics/1)
-- Logic digest: 91a23ad742858028ac5d50195304c533a2ef7b50d25f63acb5fb8f991c557419
-- Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78
-- Mode: decision
--
-- Read-only: this file contains only WITH / VALUES / SELECT statements. No DDL, DML,
-- procedures, credentials, network access, or database changes. The expressions are pure
-- Boolean expressions, so their result does not depend on SQL evaluation order.
--
-- NON-NULL INPUT PRECONDITION: NULL is not a truth value of this rule. Every fragment below
-- is defined only when every input column it reads is a non-NULL boolean. The guard template
-- (section 2) marks any NULL input as 'invalid_input' and any row that violates the
-- assumptions as 'out_of_scope', and fills output columns only for 'ok' rows; a NULL in an
-- output column of another row is an envelope marker, not a third truth value. Never wrap
-- the fragments in COALESCE(..., FALSE) or otherwise choose a meaning for unknown inputs.
-- This evaluates the supplied model; it does not show that the model is a complete, legal,
-- or safe statement of a real-world rule.
--
-- Input columns (stable ID: name -> column):
--   v_0fc060df0343: member -> "in_member"
--   v_f56b70a5523e: invited -> "in_invited"
--   v_8d70674fa3c9: banned -> "in_banned"
-- Output columns:
--   f_c04b24230e13: intended -> "out_intended"
--   f_e966114fcb43: slip -> "out_slip"
-- Assumptions (scope K; exported separately and never folded into an output):
--   none; every complete input row is in scope.

-- ----------------------------------------------------------------------------------------------
-- 1. Expression fragments (parenthesised; non-NULL boolean inputs required)
-- ----------------------------------------------------------------------------------------------
--
-- [out_intended] output intended (stable ID f_c04b24230e13)
--   intended := (member OR invited) AND NOT banned
--   PRECONDITION: "in_member", "in_invited", "in_banned" are non-NULL booleans.
--   (("in_member" OR "in_invited") AND (NOT "in_banned"))
--
-- [out_slip] output slip (stable ID f_e966114fcb43)
--   slip := member OR (invited AND NOT banned)
--   PRECONDITION: "in_member", "in_invited", "in_banned" are non-NULL booleans.
--   ("in_member" OR ("in_invited" AND (NOT "in_banned")))
--

-- ----------------------------------------------------------------------------------------------
-- 2. Guard template (read-only SELECT over an inputs list)
-- ----------------------------------------------------------------------------------------------
-- Replace the example rows between the markers with your own rows, or replace the inputs
-- CTE with a SELECT that provides the boolean columns listed in the header. status is
-- 'invalid_input' when any input is NULL, 'out_of_scope' when the assumptions are false, and
-- 'ok' otherwise; output columns are filled only for 'ok' rows (NULL elsewhere is an
-- envelope marker). Assumption columns are shown for rows with complete inputs.
WITH inputs ("row_id", "in_member", "in_invited", "in_banned") AS (
  -- tangibool:example-rows:begin
  VALUES
    (1, FALSE, FALSE, FALSE),
    (2, FALSE, FALSE, TRUE),
    (3, FALSE, TRUE, FALSE),
    (4, FALSE, TRUE, TRUE),
    (5, TRUE, FALSE, FALSE),
    (6, TRUE, FALSE, TRUE),
    (7, TRUE, TRUE, FALSE),
    (8, TRUE, TRUE, TRUE),
    (9, NULL::boolean, FALSE, FALSE)
  -- tangibool:example-rows:end
),
checked AS (
  SELECT
    inputs.*,
    CASE
      WHEN "in_member" IS NULL OR "in_invited" IS NULL OR "in_banned" IS NULL THEN 'invalid_input'
      ELSE 'ok'
    END AS "status"
  FROM inputs
)
SELECT
  "row_id",
  "in_member",
  "in_invited",
  "in_banned",
  "status",
  CASE WHEN "status" = 'ok' THEN (("in_member" OR "in_invited") AND (NOT "in_banned")) END AS "out_intended",
  CASE WHEN "status" = 'ok' THEN ("in_member" OR ("in_invited" AND (NOT "in_banned"))) END AS "out_slip"
FROM checked
ORDER BY "row_id";
SMT-LIB
; Tangibool SMT-LIB export (tangibool.smtlib/1)
; Profile: SMT-LIB 2.6 Boolean subset (QF_UF): Bool constants, define-fun, let, push/pop, assert, check-sat, echo.
; Tested with Z3 5.1.0 (z3-solver 5.2.0, WebAssembly build).
; Model: not stated
; Source revision: reference
; Interpretation status: not stated
; Exporter: 1.0.0 (engine 1.0.0; semantics tangibool-semantics/1)
; Logic digest: 91a23ad742858028ac5d50195304c533a2ef7b50d25f63acb5fb8f991c557419
; Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78
; Mode: decision
;
; Reading results: each query block states what sat and unsat mean for its question. A sat
; answer comes with a witness or counterexample (ask for it with (get-model) after sat only);
; unsat settles that scoped query and is solver-checked, not an independently checked proof
; certificate; unknown settles nothing. Blocks are scoped with push/pop, so assertions never
; accumulate across questions. This checks the supplied model, not whether it is a complete,
; legal, or safe statement of a real-world rule.
;
; Symbols (stable ID: name -> symbol):
;   v_0fc060df0343: member -> in_member
;   v_f56b70a5523e: invited -> in_invited
;   v_8d70674fa3c9: banned -> in_banned
;   f_c04b24230e13: intended -> out_intended
;   f_e966114fcb43: slip -> out_slip

(set-option :produce-models true)
(set-info :smt-lib-version 2.6)
(set-logic QF_UF)

; ---- Inputs (declared order)
(declare-const in_member Bool) ; member
(declare-const in_invited Bool) ; invited
(declare-const in_banned Bool) ; banned

; ---- Outputs (dependencies first)
; output intended (stable ID f_c04b24230e13): (member OR invited) AND NOT banned
(define-fun out_intended () Bool (and (or in_member in_invited) (not in_banned)))
; output slip (stable ID f_e966114fcb43): member OR (invited AND NOT banned)
(define-fun out_slip () Bool (or in_member (and in_invited (not in_banned))))

; ---- Assumptions (the scope K; never folded into an output)
; K: conjunction of the enabled, confirmed assumptions (true when there are none)
(define-fun K () Bool true)

; ---- Definitions only: nothing is asserted and no check is run.
; Add (assert ...) and (check-sat) inside (push 1) ... (pop 1) to ask a question.
LaTeX
intended = \left(\mathit{member} + \mathit{invited}\right) \cdot \overline{\mathit{banned}}
slip = \mathit{member} + \left(\mathit{invited} \cdot \overline{\mathit{banned}}\right)

El error habitual

Probar la regla solo con los casos felices. Los socios entran, los invitados entran, los desconocidos se quedan fuera, y las dos fórmulas aprueban. El contraejemplo es el socio vetado, member = VERDADERO, invited = FALSO, banned = VERDADERO, un caso que a nadie se le ocurrió hasta que la tabla exhaustiva lo produjo.

Preguntas

¿Alguna vez el error es la regla que realmente quieres?

Solo si los socios están de verdad exentos del veto, que es una decisión de política, no de lógica. La tabla hace visible esa política: member OR (invited AND NOT banned) admite socios vetados en dos de las ocho filas. Si es lo previsto, dilo en el glosario; si no, añade los paréntesis.

Relacionado

Operadores y compuertas

Herramientas

Véase también

Ejemplos resueltos

Generado a partir del motor de Tangibool, semántica tangibool-semantics/1, motor 1.0.0, compilación . Cada tabla, mapa, simplificación y veredicto de estas páginas lo calculó el motor de Tangibool al compilar el sitio, y cada afirmación la volvió a comprobar el mismo verificador exacto que usa la app. Los límites se indican donde aplican. © 2026 Foreranger LTD.