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Paridad impar de tres entradas: A XOR B XOR C

La paridad impar, A XOR B XOR C, es verdadera cuando un número impar de entradas lo es. La tabla, las formas normales de cuatro términos y un mapa de Karnaugh sin unos adyacentes muestran por qué las cadenas de XOR no se acortan.

Un bit de paridad protege un mensaje: el emisor lo fija para que el número total de unos sea impar, y el receptor lo recalcula. Con tres entradas la función es el XOR encadenado, y la lectura del motor enuncia la regla sin rodeos: odd_parity es verdadero exactamente cuando un número impar de A, B y C son verdaderos, uno o tres de ellos. La tabla de verdad tiene ocho filas y la salida es verdadera en cuatro, Σm(1, 2, 4, 7), las filas con una entrada verdadera y la fila con las tres.

Las comprobaciones: no es tautología, contraejemplo A = FALSO, B = FALSO, C = FALSO; es satisfacible, testigo A = FALSO, B = FALSO, C = VERDADERO. El simplificador no encontró ninguna ley que acorte la expresión de dos operadores. El conversor a formas normales, con dos eliminaciones de XOR y dos distributividades, produce una FND de cuatro términos de tres literales y una FNC de cuatro cláusulas de tres literales, doce literales en cada forma. El mapa de Karnaugh dibuja cuatro grupos de una sola celda, las celdas 1, 2, 4 y 7, cuatro implicantes primos: ningún par de unos comparte arista. Recuentos de compuertas: 20 NAND, 41 NOR.

La paridad aparece en la detección de errores de memoria, en los protocolos serie y en las sumas de comprobación, y en software como la imparidad del recuento de indicadores. Lo que hay que vigilar es el nombre: un XOR de tres entradas es paridad, no «exactamente uno», y los dos difieren cuando las tres entradas son verdaderas. La página de «exactamente uno» muestra esa fila. Como cada término de la FND menciona todas las variables, la función de paridad es también el ejemplo clásico de función que los mapas de Karnaugh no pueden acortar, cosa que conviene saber antes de dedicar tiempo al mapa.

odd_parity := A XOR B XOR C · salida

Comprobaciones exactas

¿Siempre verdadera (tautología)? No Contraejemplo: A = F, B = F, C = F · Exhaustively checked and solver cross-checked · 1 filas
¿Siempre falsa (contradicción)? No Contraejemplo: A = F, B = F, C = V · Exhaustively checked and solver cross-checked · 2 filas
¿Puede ser verdadera? Sí Asignación de ejemplo: A = F, B = F, C = V · Exhaustively checked and solver cross-checked · 2 filas

Tabla de verdad (8 filas)

Paridad impar de tres entradas: A XOR B XOR C
#ABCodd_parity
0FALSOFALSOFALSOFALSO
1FALSOFALSOVERDADEROVERDADERO
2FALSOVERDADEROFALSOVERDADERO
3FALSOVERDADEROVERDADEROFALSO
4VERDADEROFALSOFALSOVERDADERO
5VERDADEROFALSOVERDADEROFALSO
6VERDADEROVERDADEROFALSOFALSO
7VERDADEROVERDADEROVERDADEROVERDADERO

Lectura en lenguaje claro

Principianteodd_parity es verdadero exactamente cuando un número impar entre A, B y C son verdaderos (1 o 3 de ellos).
En todos los demás casos, odd_parity es falso.
Sobre los operadores:
- Una cadena de XOR es verdadera cuando un número impar de sus partes son verdaderas. Con tres partes, el caso en que las tres son verdaderas también cuenta: no significa «exactamente una».
Intermedioodd_parity es verdadero exactamente cuando un número impar entre A, B y C son verdaderos (1 o 3 de ellos).
En todos los demás casos, odd_parity es falso.
Avanzadoodd_parity es verdadero exactamente cuando un número impar entre A, B y C son verdaderos (1 o 3 de ellos) [paridad: disyunción exclusiva n-aria ⊕].
En todos los demás casos, odd_parity es falso.
Notación formal: A ⊕ B ⊕ C

Diagrama lógico

Odd parity of three inputs: A XOR B XOR C Odd parity of three inputs: A XOR B XOR C A B C odd_parity XOR
Odd parity of three inputs: A XOR B XOR C Odd parity of three inputs: A XOR B XOR C A B C odd_parity XOR

Simplificación paso a paso

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

A XOR B XOR C

Mapa de Karnaugh

A \ BC
00
01
11
10
0
0m0
1m1
0m3
1m2
1
1m4
0m5
1m7
0m6
  1. celdas m1NOT A AND NOT B AND C
  2. celdas m2NOT A AND B AND NOT C
  3. celdas m4A AND NOT B AND NOT C
  4. celdas m7A AND B AND C
(NOT A AND NOT B AND C) OR (NOT A AND B AND NOT C) OR (A AND NOT B AND NOT C) OR (A AND B AND C) · Derived (NOT A AND NOT B AND C) OR (NOT A AND B AND NOT C) OR (A AND NOT B AND NOT C) OR (A AND B AND C). Exactly equivalent on every assignment.

Mintérminos y maxtérminos

odd_parity(A, B, C) = Σm(1, 2, 4, 7)odd_parity(A, B, C) = ΠM(0, 3, 5, 6)

Orden de variables: A, B, C · 8 filas

Formas normales

Forma normal conjuntiva (FNC)

(A OR B OR C) AND (A OR NOT B OR NOT C) AND (NOT A OR B OR NOT C) AND (NOT A OR NOT B OR C)

4 cláusulas, 12 literales · complete · Eliminación de XOR ×2, Distributividad ×2

Forma normal disyuntiva (FND)

(A AND B AND C) OR (A AND NOT B AND NOT C) OR (NOT A AND B AND NOT C) OR (NOT A AND NOT B AND C)

4 términos, 12 literales · complete · Eliminación de XOR ×2, Distributividad ×2

Solo NAND, solo NOR

Forma solo con NAND

NAND(NAND(NAND(NAND(A, NAND(B, B)), NAND(NAND(A, A), B)), NAND(C, C)), NAND(NAND(NAND(NAND(A, NAND(B, B)), NAND(NAND(A, A), B)), NAND(NAND(A, NAND(B, B)), NAND(NAND(A, A), B))), C))

20 compuertas · equivalencia verificada en todas las filas

Forma solo con NOR

NOR(NOR(NOR(NOR(NOR(NOR(A, A), B), NOR(A, NOR(B, B))), C), NOR(NOR(NOR(NOR(NOR(A, A), B), NOR(A, NOR(B, B))), NOR(NOR(NOR(A, A), B), NOR(A, NOR(B, B)))), NOR(C, C))), NOR(NOR(NOR(NOR(NOR(A, A), B), NOR(A, NOR(B, B))), C), NOR(NOR(NOR(NOR(NOR(A, A), B), NOR(A, NOR(B, B))), NOR(NOR(NOR(A, A), B), NOR(A, NOR(B, B)))), NOR(C, C))))

41 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: 7875b852c61b8ea8b990b3327315b496608f22bf11c48c8fa0e14b6391c0ecf9
Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78

Inputs (dict keys, declared order) and generated parameter names:
    'A' -> input_A
    'B' -> input_B
    'C' -> input_C

Outputs (declared order) and their functions:
    'odd_parity' -> output_odd_parity(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({'A': False, 'B': False, 'C': False})
    # -> {'odd_parity': False}
    model.output_odd_parity({'A': False, 'B': False, 'C': False})
    # -> False
    model.evaluate({'A': 1, 'B': False, 'C': 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_odd_parity",
]

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": "7875b852c61b8ea8b990b3327315b496608f22bf11c48c8fa0e14b6391c0ecf9",
    "assumptions_digest": "d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78",
    "primary_output": "odd_parity",
    "unused_inputs": (),
    "subcircuits": (),
}

# Stable ID -> generated identifier (reversible mapping; names are exact, escaped strings).
IDENTIFIER_MAP = {
    "v_1e593d4093c7": {"kind": "input", "name": "A", "identifier": "input_A"},
    "v_3c7b7802ca65": {"kind": "input", "name": "B", "identifier": "input_B"},
    "v_b5fa346da697": {"kind": "input", "name": "C", "identifier": "input_C"},
    "f_b09a68d3f674": {"kind": "output", "name": "odd_parity", "identifier": "output_odd_parity"},
}

INPUT_NAMES = ("A", "B", "C")
OUTPUT_NAMES = ("odd_parity",)
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_odd_parity(input_A: bool, input_B: bool, input_C: bool) -> bool:
    """Decision output 'odd_parity': A XOR B XOR C"""
    return (input_A != input_B) != input_C


# ---- Public API ----


def output_odd_parity(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'odd_parity' (stable ID f_b09a68d3f674).

    'odd_parity' := A XOR B XOR C

    Required inputs: 'A', 'B', 'C'.
    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, ("A", "B", "C"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_odd_parity_value = _compute_output_odd_parity(values["A"], values["B"], values["C"])
    return output_odd_parity_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: 'A', 'B', 'C'.
    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, ("A", "B", "C"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_odd_parity_value = _compute_output_odd_parity(values["A"], values["B"], values["C"])
    return {
        "odd_parity": output_odd_parity_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: 7875b852c61b8ea8b990b3327315b496608f22bf11c48c8fa0e14b6391c0ecf9
-- 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_1e593d4093c7: A -> "in_A"
--   v_3c7b7802ca65: B -> "in_B"
--   v_b5fa346da697: C -> "in_C"
-- Output columns:
--   f_b09a68d3f674: odd_parity -> "out_odd_parity"
-- 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_odd_parity] output odd_parity (stable ID f_b09a68d3f674)
--   odd_parity := A XOR B XOR C
--   PRECONDITION: "in_A", "in_B", "in_C" are non-NULL booleans.
--   (("in_A" <> "in_B") <> "in_C")
--

-- ----------------------------------------------------------------------------------------------
-- 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_A", "in_B", "in_C") 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_A" IS NULL OR "in_B" IS NULL OR "in_C" IS NULL THEN 'invalid_input'
      ELSE 'ok'
    END AS "status"
  FROM inputs
)
SELECT
  "row_id",
  "in_A",
  "in_B",
  "in_C",
  "status",
  CASE WHEN "status" = 'ok' THEN (("in_A" <> "in_B") <> "in_C") END AS "out_odd_parity"
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: 7875b852c61b8ea8b990b3327315b496608f22bf11c48c8fa0e14b6391c0ecf9
; 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_1e593d4093c7: A -> in_A
;   v_3c7b7802ca65: B -> in_B
;   v_b5fa346da697: C -> in_C
;   f_b09a68d3f674: odd_parity -> out_odd_parity

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

; ---- Inputs (declared order)
(declare-const in_A Bool) ; A
(declare-const in_B Bool) ; B
(declare-const in_C Bool) ; C

; ---- Outputs (dependencies first)
; output odd_parity (stable ID f_b09a68d3f674): A XOR B XOR C
(define-fun out_odd_parity () Bool (xor (xor in_A in_B) in_C))

; ---- 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
odd_parity = A \oplus B \oplus C

El error habitual

Leer A XOR B XOR C como «exactamente uno de los tres». La tabla dice lo contrario en su última fila: con A = VERDADERO, B = VERDADERO, C = VERDADERO la cadena es verdadera, porque tres es impar. Una fórmula para «exactamente uno» necesita la forma AND-OR de la página compañera.

Preguntas

¿Por qué el mapa tiene cuatro grupos separados?

Las celdas verdaderas son 1, 2, 4 y 7, y cada una difiere de las demás en al menos dos variables, así que ninguna es adyacente a otra en el mapa. Cada celda es su propio implicante primo, y la expresión derivada es la suma de mintérminos de cuatro términos.

¿Importa cómo se agrupan los XOR?

No. XOR es asociativo y conmutativo, así que A XOR (B XOR C) y (A XOR B) XOR C dan la misma columna. La página de la suma del sumador completo usa la misma función con el acarreo de entrada como tercera entrada.

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.