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Semisumador, suma: A XOR B

El bit de suma de un semisumador es A XOR B, mostrado junto a su acarreo A AND B. Cuatro filas, las formas normales por eliminación de XOR, un mapa de Karnaugh de dos celdas y la construcción NAND de 5 compuertas.

Un semisumador suma dos números de un bit. El bit de suma es 1 cuando exactamente una entrada es 1, que es XOR; el bit de acarreo es 1 cuando lo son las dos, que es AND. El modelo lleva las dos salidas para que la tabla las muestre una junto a otra: sum es verdadero en las filas 1 y 2, Σm(1, 2), y carry solo en la fila 3. La lectura del motor para la suma es la definición de manual: verdadero exactamente cuando exactamente uno entre A y B es verdadero, no ambos.

Para la suma, la tautología se viola con el contraejemplo A = FALSO, B = FALSO, y la satisfacibilidad se cumple con el testigo A = FALSO, B = VERDADERO. El simplificador no encontró ninguna ley que acorte A XOR B, ya un solo operador. El conversor a formas normales usa una eliminación de XOR: la FND es (A AND NOT B) OR (NOT A AND B) y la FNC es (A OR B) AND (NOT A OR NOT B), dos términos y cuatro literales cada una. El mapa de Karnaugh dibuja dos grupos de una celda, las celdas 1 y 2, dos implicantes primos. Compuertas: 5 NAND, 11 NOR.

El semisumador es el primer circuito de cualquier curso de diseño digital y la base de todo sumador con acarreo en cascada, donde toman el relevo las páginas del sumador completo. En software el mismo XOR aparece como un conmutador, un indicador de diferencia o una suma de comprobación de un bit. Lo que hay que vigilar es que la suma por sí sola pierde información: las filas 0 y 3 dan las dos sum = FALSO, y solo la columna del acarreo distingue 0 + 0 de 1 + 1. Lee siempre las dos columnas juntas.

sum := A XOR B · salidacarry := A AND B · salida

Comprobaciones exactas

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

Tabla de verdad (4 filas)

Semisumador, suma: A XOR B
#ABsumcarry
0FALSOFALSOFALSOFALSO
1FALSOVERDADEROVERDADEROFALSO
2VERDADEROFALSOVERDADEROFALSO
3VERDADEROVERDADEROFALSOVERDADERO

Lectura en lenguaje claro

Principiantesum es verdadero exactamente cuando exactamente uno entre A y B es verdadero (no ambos).
En todos los demás casos, sum es falso.
Sobre los operadores:
- XOR (O exclusivo) es verdadero cuando exactamente una de sus dos partes es verdadera.
Intermediosum es verdadero exactamente cuando exactamente uno entre A y B es verdadero (no ambos).
En todos los demás casos, sum es falso.
Avanzadosum es verdadero exactamente cuando exactamente uno entre A y B es verdadero (no ambos) [disyunción exclusiva ⊕].
En todos los demás casos, sum es falso.
Notación formal: A ⊕ B

Diagrama lógico

Half adder sum: A XOR B Half adder sum: A XOR B A B sumPRIMARY carry XOR AND
Half adder sum: A XOR B Half adder sum: A XOR B A B sumPRIMARY carry XOR AND

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

Mapa de Karnaugh

A \ B
0
1
0
0m0
1m1
1
1m2
0m3
  1. celdas m1NOT A AND B
  2. celdas m2A AND NOT B
(NOT A AND B) OR (A AND NOT B) · Derived (NOT A AND B) OR (A AND NOT B). Exactly equivalent on every assignment.

Mintérminos y maxtérminos

sum(A, B) = Σm(1, 2)sum(A, B) = ΠM(0, 3)

Orden de variables: A, B · 4 filas

Formas normales

Forma normal conjuntiva (FNC)

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

2 cláusulas, 4 literales · complete · Eliminación de XOR ×1

Forma normal disyuntiva (FND)

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

2 términos, 4 literales · complete · Eliminación de XOR ×1

Solo NAND, solo NOR

Forma solo con NAND

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

5 compuertas · equivalencia verificada en todas las filas

Forma solo con NOR

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

11 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: d024e24759c1c767e4cbed2597268e2b229376895bb574c5806ad923cfbd7115
Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78

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

Outputs (declared order) and their functions:
    'sum' -> output_sum(inputs)
    'carry' -> output_carry(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})
    # -> {'sum': False, 'carry': False}
    model.output_sum({'A': False, 'B': False})
    # -> False
    model.evaluate({'A': 1, 'B': 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_sum",
    "output_carry",
]

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": "d024e24759c1c767e4cbed2597268e2b229376895bb574c5806ad923cfbd7115",
    "assumptions_digest": "d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78",
    "primary_output": "sum",
    "unused_inputs": (),
    "subcircuits": (),
}

# Stable ID -> generated identifier (reversible mapping; names are exact, escaped strings).
IDENTIFIER_MAP = {
    "v_43b46acabf3a": {"kind": "input", "name": "A", "identifier": "input_A"},
    "v_3b9837272ba1": {"kind": "input", "name": "B", "identifier": "input_B"},
    "f_91ff4e74d116": {"kind": "output", "name": "sum", "identifier": "output_sum"},
    "f_b75eceb1da79": {"kind": "output", "name": "carry", "identifier": "output_carry"},
}

INPUT_NAMES = ("A", "B")
OUTPUT_NAMES = ("sum", "carry")
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_sum(input_A: bool, input_B: bool) -> bool:
    """Decision output 'sum': A XOR B"""
    return input_A != input_B


def _compute_output_carry(input_A: bool, input_B: bool) -> bool:
    """Decision output 'carry': A AND B"""
    return input_A and input_B


# ---- Public API ----


def output_sum(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'sum' (stable ID f_91ff4e74d116).

    'sum' := A XOR B

    Required inputs: 'A', 'B'.
    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"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_sum_value = _compute_output_sum(values["A"], values["B"])
    return output_sum_value


def output_carry(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'carry' (stable ID f_b75eceb1da79).

    'carry' := A AND B

    Required inputs: 'A', 'B'.
    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"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_carry_value = _compute_output_carry(values["A"], values["B"])
    return output_carry_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'.
    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"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_sum_value = _compute_output_sum(values["A"], values["B"])
    output_carry_value = _compute_output_carry(values["A"], values["B"])
    return {
        "sum": output_sum_value,
        "carry": output_carry_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: d024e24759c1c767e4cbed2597268e2b229376895bb574c5806ad923cfbd7115
-- 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_43b46acabf3a: A -> "in_A"
--   v_3b9837272ba1: B -> "in_B"
-- Output columns:
--   f_91ff4e74d116: sum -> "out_sum"
--   f_b75eceb1da79: carry -> "out_carry"
-- 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_sum] output sum (stable ID f_91ff4e74d116)
--   sum := A XOR B
--   PRECONDITION: "in_A", "in_B" are non-NULL booleans.
--   ("in_A" <> "in_B")
--
-- [out_carry] output carry (stable ID f_b75eceb1da79)
--   carry := A AND B
--   PRECONDITION: "in_A", "in_B" are non-NULL booleans.
--   ("in_A" AND "in_B")
--

-- ----------------------------------------------------------------------------------------------
-- 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") AS (
  -- tangibool:example-rows:begin
  VALUES
    (1, FALSE, FALSE),
    (2, FALSE, TRUE),
    (3, TRUE, FALSE),
    (4, TRUE, TRUE),
    (5, NULL::boolean, FALSE)
  -- tangibool:example-rows:end
),
checked AS (
  SELECT
    inputs.*,
    CASE
      WHEN "in_A" IS NULL OR "in_B" IS NULL THEN 'invalid_input'
      ELSE 'ok'
    END AS "status"
  FROM inputs
)
SELECT
  "row_id",
  "in_A",
  "in_B",
  "status",
  CASE WHEN "status" = 'ok' THEN ("in_A" <> "in_B") END AS "out_sum",
  CASE WHEN "status" = 'ok' THEN ("in_A" AND "in_B") END AS "out_carry"
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: d024e24759c1c767e4cbed2597268e2b229376895bb574c5806ad923cfbd7115
; 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_43b46acabf3a: A -> in_A
;   v_3b9837272ba1: B -> in_B
;   f_91ff4e74d116: sum -> out_sum
;   f_b75eceb1da79: carry -> out_carry

(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

; ---- Outputs (dependencies first)
; output sum (stable ID f_91ff4e74d116): A XOR B
(define-fun out_sum () Bool (xor in_A in_B))
; output carry (stable ID f_b75eceb1da79): A AND B
(define-fun out_carry () Bool (and in_A in_B))

; ---- 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
sum = A \oplus B
carry = A \cdot B

El error habitual

Construir la suma con OR en vez de XOR. A OR B coincide con A XOR B en tres filas y difiere en A = VERDADERO, B = VERDADERO, donde la suma debe ser 0 con acarreo 1. La tabla hace evidente la fila verdadera de más; un sumador construido así calcula 1 + 1 = 3.

Preguntas

¿Por qué la FND tiene cuatro literales si la fórmula tiene dos?

XOR no es una primitiva AND-OR, así que el conversor lo reescribe por eliminación de XOR en los dos casos en que las entradas difieren. Cada caso nombra las dos entradas, de ahí los cuatro literales. La tabla confirma la reescritura en las cuatro filas.

¿Es 5 el menor número posible de compuertas NAND para XOR?

La construcción mecánica del conversor usa 5; el circuito clásico dibujado a mano usa 4, y la página del XOR solo con NAND prueba que ese circuito equivale a A XOR B. El conversor etiqueta su salida como una construcción, no como la más corta.

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.