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Regla de envío gratis: (mas_de_50 OR prime) AND NOT voluminoso AND nacional

Una regla de envío, (over_50 OR prime) AND NOT oversized AND domestic: dieciséis filas con tres que cumplen, una FND de dos términos, y una forma NOR de 7 compuertas frente a 25 NAND.

El envío es gratis para pedidos de más de cincuenta o para clientes prime, siempre que el paquete no sea voluminoso y la dirección sea nacional. La lectura del motor enumera los tres requisitos: al menos uno entre over_50 y prime, oversized falso, domestic verdadero. En la tabla de dieciséis filas la salida es verdadera en tres filas, Σm(5, 9, 13): solo prime, solo más de cincuenta, o ambos, cada una con un paquete de tamaño normal a una dirección nacional.

Las comprobaciones: no es tautología, contraejemplo las cuatro entradas en FALSO; satisfacible, testigo over_50 = FALSO, prime = VERDADERO, oversized = FALSO, domestic = VERDADERO. El simplificador no encontró ninguna ley que acorte la regla de cuatro operadores; la FNC es la original, tres cláusulas. El conversor a FND aplica dos distributividades y da (over_50 AND NOT oversized AND domestic) OR (prime AND NOT oversized AND domestic), dos términos y seis literales; el mapa deriva lo mismo de dos grupos, dos implicantes primos. Compuertas: 25 NAND y 7 NOR, el desequilibrio habitual de un OR que alimenta un AND con una entrada negada.

Las reglas de caja con esta forma se reescriben a menudo, según van y vienen las promociones, y cada reescritura es una ocasión de cambiar las tres filas verdaderas sin querer. Lo que hay que vigilar son los dos bloqueos: oversized está negado y domestic no, y es fácil intercambiarlos al transcribir la regla a un motor de precios. La fila del testigo, un cliente prime con un paquete normal nacional, es una buena prueba de humo, y las tres filas verdaderas juntas son la batería positiva completa.

free_shipping := (over_50 OR prime) AND NOT oversized AND domestic · salida

Comprobaciones exactas

¿Siempre verdadera (tautología)? No Contraejemplo: over_50 = F, prime = F, oversized = F, domestic = F · Exhaustively checked and solver cross-checked · 1 filas
¿Siempre falsa (contradicción)? No Contraejemplo: over_50 = F, prime = V, oversized = F, domestic = V · Exhaustively checked and solver cross-checked · 6 filas
¿Puede ser verdadera? Sí Asignación de ejemplo: over_50 = F, prime = V, oversized = F, domestic = V · Exhaustively checked and solver cross-checked · 6 filas

Tabla de verdad (16 filas)

Regla de envío gratis: (mas_de_50 OR prime) AND NOT voluminoso AND nacional
#over_50primeoversizeddomesticfree_shipping
0FALSOFALSOFALSOFALSOFALSO
1FALSOFALSOFALSOVERDADEROFALSO
2FALSOFALSOVERDADEROFALSOFALSO
3FALSOFALSOVERDADEROVERDADEROFALSO
4FALSOVERDADEROFALSOFALSOFALSO
5FALSOVERDADEROFALSOVERDADEROVERDADERO
6FALSOVERDADEROVERDADEROFALSOFALSO
7FALSOVERDADEROVERDADEROVERDADEROFALSO
8VERDADEROFALSOFALSOFALSOFALSO
9VERDADEROFALSOFALSOVERDADEROVERDADERO
10VERDADEROFALSOVERDADEROFALSOFALSO
11VERDADEROFALSOVERDADEROVERDADEROFALSO
12VERDADEROVERDADEROFALSOFALSOFALSO
13VERDADEROVERDADEROFALSOVERDADEROVERDADERO
14VERDADEROVERDADEROVERDADEROFALSOFALSO
15VERDADEROVERDADEROVERDADEROVERDADEROFALSO

Lectura en lenguaje claro

Principiantefree_shipping es verdadero exactamente cuando se cumplen todas las condiciones siguientes:
1. al menos uno entre over_50 y prime es verdadero (pueden serlo ambos)
2. oversized es falso
3. domestic es verdadero
En todos los demás casos, free_shipping 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.
Intermediofree_shipping es verdadero exactamente cuando se cumplen todas las condiciones siguientes:
1. al menos uno entre over_50 y prime es verdadero (pueden serlo ambos)
2. oversized es falso
3. domestic es verdadero
En todos los demás casos, free_shipping es falso.
Avanzadofree_shipping es verdadero exactamente cuando se cumplen todas las condiciones siguientes [conjunción ∧]:
1. al menos uno entre over_50 y prime es verdadero (pueden serlo ambos) [disyunción inclusiva ∨]
2. oversized es falso [negación ¬]
3. domestic es verdadero
En todos los demás casos, free_shipping es falso.
Notación formal: (over_50 ∨ prime) ∧ ¬oversized ∧ domestic

Diagrama lógico

Free shipping rule: (over_50 OR prime) AND NOT oversized AND domestic Free shipping rule: (over_50 OR prime) AND NOT oversized AND domestic over_50 prime oversized domestic free_shipping AND OR NOT
Free shipping rule: (over_50 OR prime) AND NOT oversized AND domestic Free shipping rule: (over_50 OR prime) AND NOT oversized AND domestic over_50 prime oversized domestic free_shipping AND OR 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.

(over_50 OR prime) AND NOT oversized AND domestic

Mapa de Karnaugh

over_50prime \ oversizeddomestic
00
01
11
10
00
0m0
0m1
0m3
0m2
01
0m4
1m5
0m7
0m6
11
0m12
1m13
0m15
0m14
10
0m8
1m9
0m11
0m10
  1. celdas m9, m13over_50 AND NOT oversized AND domestic
  2. celdas m5, m13prime AND NOT oversized AND domestic
(over_50 AND NOT oversized AND domestic) OR (prime AND NOT oversized AND domestic) · Derived (over_50 AND NOT oversized AND domestic) OR (prime AND NOT oversized AND domestic). Exactly equivalent on every assignment.

Mintérminos y maxtérminos

free_shipping(over_50, prime, oversized, domestic) = Σm(5, 9, 13)free_shipping(over_50, prime, oversized, domestic) = ΠM(0, 1, 2, 3, 4, 6, 7, 8, 10, 11, 12, 14, 15)

Orden de variables: over_50, prime, oversized, domestic · 16 filas

Formas normales

Forma normal conjuntiva (FNC)

(over_50 OR prime) AND NOT oversized AND domestic

3 cláusulas, 4 literales · complete

Forma normal disyuntiva (FND)

(over_50 AND NOT oversized AND domestic) OR (prime AND NOT oversized AND domestic)

2 términos, 6 literales · complete · Distributividad ×2

Solo NAND, solo NOR

Forma solo con NAND

NAND(NAND(NAND(NAND(NAND(NAND(over_50, over_50), NAND(prime, prime)), NAND(oversized, oversized)), NAND(NAND(NAND(over_50, over_50), NAND(prime, prime)), NAND(oversized, oversized))), domestic), NAND(NAND(NAND(NAND(NAND(over_50, over_50), NAND(prime, prime)), NAND(oversized, oversized)), NAND(NAND(NAND(over_50, over_50), NAND(prime, prime)), NAND(oversized, oversized))), domestic))

25 compuertas · equivalencia verificada en todas las filas

Forma solo con NOR

NOR(NOR(NOR(NOR(over_50, prime), oversized), NOR(NOR(over_50, prime), oversized)), NOR(domestic, domestic))

7 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: 06b94ace715e24da7f488742835d4637399ac84b8c8d35b085821515e815163c
Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78

Inputs (dict keys, declared order) and generated parameter names:
    'over_50' -> input_over_50
    'prime' -> input_prime
    'oversized' -> input_oversized
    'domestic' -> input_domestic

Outputs (declared order) and their functions:
    'free_shipping' -> output_free_shipping(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({'over_50': False, 'prime': False, 'oversized': False, 'domestic': False})
    # -> {'free_shipping': False}
    model.output_free_shipping({'over_50': False, 'prime': False, 'oversized': False, 'domestic': False})
    # -> False
    model.evaluate({'over_50': 1, 'prime': False, 'oversized': False, 'domestic': 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_free_shipping",
]

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": "06b94ace715e24da7f488742835d4637399ac84b8c8d35b085821515e815163c",
    "assumptions_digest": "d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78",
    "primary_output": "free_shipping",
    "unused_inputs": (),
    "subcircuits": (),
}

# Stable ID -> generated identifier (reversible mapping; names are exact, escaped strings).
IDENTIFIER_MAP = {
    "v_c5a612b01b69": {"kind": "input", "name": "over_50", "identifier": "input_over_50"},
    "v_f6de1dea7c06": {"kind": "input", "name": "prime", "identifier": "input_prime"},
    "v_5f92878a5d47": {"kind": "input", "name": "oversized", "identifier": "input_oversized"},
    "v_edf6f5fd2f11": {"kind": "input", "name": "domestic", "identifier": "input_domestic"},
    "f_075d3af2c11d": {"kind": "output", "name": "free_shipping", "identifier": "output_free_shipping"},
}

INPUT_NAMES = ("over_50", "prime", "oversized", "domestic")
OUTPUT_NAMES = ("free_shipping",)
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_free_shipping(input_over_50: bool, input_prime: bool, input_oversized: bool, input_domestic: bool) -> bool:
    """Decision output 'free_shipping': (over_50 OR prime) AND NOT oversized AND domestic"""
    return (input_over_50 or input_prime) and (not input_oversized) and input_domestic


# ---- Public API ----


def output_free_shipping(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'free_shipping' (stable ID f_075d3af2c11d).

    'free_shipping' := (over_50 OR prime) AND NOT oversized AND domestic

    Required inputs: 'over_50', 'prime', 'oversized', 'domestic'.
    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, ("over_50", "prime", "oversized", "domestic"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_free_shipping_value = _compute_output_free_shipping(values["over_50"], values["prime"], values["oversized"], values["domestic"])
    return output_free_shipping_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: 'over_50', 'prime', 'oversized', 'domestic'.
    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, ("over_50", "prime", "oversized", "domestic"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_free_shipping_value = _compute_output_free_shipping(values["over_50"], values["prime"], values["oversized"], values["domestic"])
    return {
        "free_shipping": output_free_shipping_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: 06b94ace715e24da7f488742835d4637399ac84b8c8d35b085821515e815163c
-- 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_c5a612b01b69: over_50 -> "in_over_50"
--   v_f6de1dea7c06: prime -> "in_prime"
--   v_5f92878a5d47: oversized -> "in_oversized"
--   v_edf6f5fd2f11: domestic -> "in_domestic"
-- Output columns:
--   f_075d3af2c11d: free_shipping -> "out_free_shipping"
-- 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_free_shipping] output free_shipping (stable ID f_075d3af2c11d)
--   free_shipping := (over_50 OR prime) AND NOT oversized AND domestic
--   PRECONDITION: "in_over_50", "in_prime", "in_oversized", "in_domestic" are non-NULL booleans.
--   (("in_over_50" OR "in_prime") AND (NOT "in_oversized") AND "in_domestic")
--

-- ----------------------------------------------------------------------------------------------
-- 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_over_50", "in_prime", "in_oversized", "in_domestic") AS (
  -- tangibool:example-rows:begin
  VALUES
    (1, FALSE, FALSE, FALSE, FALSE),
    (2, FALSE, FALSE, FALSE, TRUE),
    (3, FALSE, FALSE, TRUE, FALSE),
    (4, FALSE, FALSE, TRUE, TRUE),
    (5, FALSE, TRUE, FALSE, FALSE),
    (6, FALSE, TRUE, FALSE, TRUE),
    (7, FALSE, TRUE, TRUE, FALSE),
    (8, FALSE, TRUE, TRUE, TRUE),
    (9, TRUE, FALSE, FALSE, FALSE),
    (10, TRUE, FALSE, FALSE, TRUE),
    (11, TRUE, FALSE, TRUE, FALSE),
    (12, TRUE, FALSE, TRUE, TRUE),
    (13, TRUE, TRUE, FALSE, FALSE),
    (14, TRUE, TRUE, FALSE, TRUE),
    (15, TRUE, TRUE, TRUE, FALSE),
    (16, TRUE, TRUE, TRUE, TRUE),
    (17, NULL::boolean, FALSE, FALSE, FALSE)
  -- tangibool:example-rows:end
),
checked AS (
  SELECT
    inputs.*,
    CASE
      WHEN "in_over_50" IS NULL OR "in_prime" IS NULL OR "in_oversized" IS NULL OR "in_domestic" IS NULL THEN 'invalid_input'
      ELSE 'ok'
    END AS "status"
  FROM inputs
)
SELECT
  "row_id",
  "in_over_50",
  "in_prime",
  "in_oversized",
  "in_domestic",
  "status",
  CASE WHEN "status" = 'ok' THEN (("in_over_50" OR "in_prime") AND (NOT "in_oversized") AND "in_domestic") END AS "out_free_shipping"
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: 06b94ace715e24da7f488742835d4637399ac84b8c8d35b085821515e815163c
; 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_c5a612b01b69: over_50 -> in_over_50
;   v_f6de1dea7c06: prime -> in_prime
;   v_5f92878a5d47: oversized -> in_oversized
;   v_edf6f5fd2f11: domestic -> in_domestic
;   f_075d3af2c11d: free_shipping -> out_free_shipping

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

; ---- Inputs (declared order)
(declare-const in_over_50 Bool) ; over_50
(declare-const in_prime Bool) ; prime
(declare-const in_oversized Bool) ; oversized
(declare-const in_domestic Bool) ; domestic

; ---- Outputs (dependencies first)
; output free_shipping (stable ID f_075d3af2c11d): (over_50 OR prime) AND NOT oversized AND domestic
(define-fun out_free_shipping () Bool (and (or in_over_50 in_prime) (not in_oversized) in_domestic))

; ---- 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
free_shipping = \left(\mathit{over\_50} + \mathit{prime}\right) \cdot \overline{\mathit{oversized}} \cdot \mathit{domestic}

El error habitual

Transcribir los dos bloqueos con la misma polaridad, NOT oversized AND NOT domestic o oversized AND domestic. Cualquiera de las dos versiones cambia las tres filas que cumplen. Las filas verdaderas de la tabla tienen todas oversized = FALSO y domestic = VERDADERO; comprobar ese par es la revisión más rápida de cualquier reimplementación.

Preguntas

¿Por qué los números de mintérmino son 5, 9 y 13?

Con over_50 como bit más significativo y domestic como el menos, una fila que cumple termina en los bits oversized = 0, domestic = 1, que aportan 1, y empieza con prime solo, 4, over_50 solo, 8, o ambos, 12. Las tres sumas son 5, 9 y 13.

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.