Regla de feature flag: (beta OR interno) AND flag_activo AND NOT interruptor
Una regla de feature flag, (beta_user OR internal) AND flag_on AND NOT kill_switch: dieciséis filas con tres que activan, una FND de dos términos, dos grupos de Karnaugh, y una forma NOR de 8 compuertas frente a 23 NAND.
La funcionalidad se activa para usuarios beta o personal interno, pero solo mientras el flag esté encendido y el interruptor de emergencia apagado. La lectura del motor enumera los tres requisitos: al menos uno entre beta_user e internal, flag_on verdadero, kill_switch falso. Con cuatro entradas la tabla tiene dieciséis filas, y la salida es verdadera en tres, Σm(6, 10, 14): un usuario interno, un usuario beta, o ambos, cada uno con el flag encendido y el interruptor apagado.
Las comprobaciones: no es tautología, contraejemplo las cuatro entradas en FALSO; satisfacible, testigo beta_user = FALSO, internal = VERDADERO, flag_on = VERDADERO, kill_switch = FALSO. El simplificador no encontró ninguna ley que acorte la regla de cuatro operadores, y el conversor a FNC la devuelve sin cambios como tres cláusulas. El conversor a FND aplica dos distributividades y da (beta_user AND flag_on AND NOT kill_switch) OR (internal AND flag_on AND NOT kill_switch), dos términos y seis literales, que es también lo que el mapa de Karnaugh deriva de sus dos grupos, en las celdas 10 y 14 y en las celdas 6 y 14, dos implicantes primos. Compuertas: 23 NAND, 8 NOR.
Las reglas de flags se evalúan en cada petición, normalmente por una biblioteca que recibe una lista de condiciones, y el fallo más frecuente es un OR de audiencia que se traga las comprobaciones de seguridad, como en la página del error de la regla de entrada. Lo que hay que vigilar aquí es el interruptor de emergencia: debe prevalecer sobre todo, lo que en la fórmula significa que va unido con AND en el nivel superior y no dentro del grupo de audiencia. Las tres filas verdaderas tienen todas kill_switch = FALSO, y esa es la propiedad que hay que afirmar en una prueba.
enabled := (beta_user OR internal) AND flag_on AND NOT kill_switch · salida
Comprobaciones exactas
Tabla de verdad (16 filas)
| # | beta_user | internal | flag_on | kill_switch | enabled |
|---|---|---|---|---|---|
| 0 | FALSO | FALSO | FALSO | FALSO | FALSO |
| 1 | FALSO | FALSO | FALSO | VERDADERO | FALSO |
| 2 | FALSO | FALSO | VERDADERO | FALSO | FALSO |
| 3 | FALSO | FALSO | VERDADERO | VERDADERO | FALSO |
| 4 | FALSO | VERDADERO | FALSO | FALSO | FALSO |
| 5 | FALSO | VERDADERO | FALSO | VERDADERO | FALSO |
| 6 | FALSO | VERDADERO | VERDADERO | FALSO | VERDADERO |
| 7 | FALSO | VERDADERO | VERDADERO | VERDADERO | FALSO |
| 8 | VERDADERO | FALSO | FALSO | FALSO | FALSO |
| 9 | VERDADERO | FALSO | FALSO | VERDADERO | FALSO |
| 10 | VERDADERO | FALSO | VERDADERO | FALSO | VERDADERO |
| 11 | VERDADERO | FALSO | VERDADERO | VERDADERO | FALSO |
| 12 | VERDADERO | VERDADERO | FALSO | FALSO | FALSO |
| 13 | VERDADERO | VERDADERO | FALSO | VERDADERO | FALSO |
| 14 | VERDADERO | VERDADERO | VERDADERO | FALSO | VERDADERO |
| 15 | VERDADERO | VERDADERO | VERDADERO | VERDADERO | FALSO |
Lectura en lenguaje claro
Principianteenabled es verdadero exactamente cuando se cumplen todas las condiciones siguientes:
1. al menos uno entre beta_user e internal es verdadero (pueden serlo ambos)
2. flag_on es verdadero
3. kill_switch es falso
En todos los demás casos, enabled 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.
Intermedioenabled es verdadero exactamente cuando se cumplen todas las condiciones siguientes:
1. al menos uno entre beta_user e internal es verdadero (pueden serlo ambos)
2. flag_on es verdadero
3. kill_switch es falso
En todos los demás casos, enabled es falso.
Avanzadoenabled es verdadero exactamente cuando se cumplen todas las condiciones siguientes [conjunción ∧]:
1. al menos uno entre beta_user e internal es verdadero (pueden serlo ambos) [disyunción inclusiva ∨]
2. flag_on es verdadero
3. kill_switch es falso [negación ¬]
En todos los demás casos, enabled es falso.
Notación formal: (beta_user ∨ internal) ∧ flag_on ∧ ¬kill_switch
Diagrama lógico
Simplificación paso a paso
El motor no encontró ninguna ley que acorte esta expresión; ya es tan corta como sus leyes de reescritura permiten.
(beta_user OR internal) AND flag_on AND NOT kill_switch
Mapa de Karnaugh
- celdas m10, m14
beta_user AND flag_on AND NOT kill_switch - celdas m6, m14
internal AND flag_on AND NOT kill_switch
Mintérminos y maxtérminos
enabled(beta_user, internal, flag_on, kill_switch) = Σm(6, 10, 14)enabled(beta_user, internal, flag_on, kill_switch) = ΠM(0, 1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 13, 15)Orden de variables: beta_user, internal, flag_on, kill_switch · 16 filas
Formas normales
Forma normal conjuntiva (FNC)
(beta_user OR internal) AND flag_on AND NOT kill_switch3 cláusulas, 4 literales · complete
Forma normal disyuntiva (FND)
(beta_user AND flag_on AND NOT kill_switch) OR (internal AND flag_on AND NOT kill_switch)2 términos, 6 literales · complete · Distributividad ×2
Solo NAND, solo NOR
Forma solo con NAND
NAND(NAND(NAND(NAND(NAND(NAND(beta_user, beta_user), NAND(internal, internal)), flag_on), NAND(NAND(NAND(beta_user, beta_user), NAND(internal, internal)), flag_on)), NAND(kill_switch, kill_switch)), NAND(NAND(NAND(NAND(NAND(beta_user, beta_user), NAND(internal, internal)), flag_on), NAND(NAND(NAND(beta_user, beta_user), NAND(internal, internal)), flag_on)), NAND(kill_switch, kill_switch)))23 compuertas · equivalencia verificada en todas las filas
Forma solo con NOR
NOR(NOR(NOR(NOR(beta_user, internal), NOR(flag_on, flag_on)), NOR(NOR(beta_user, internal), NOR(flag_on, flag_on))), kill_switch)8 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: e38bc7c67f8a857345783c8ad32faa5a9e83e9828b516a5d2f543e988edde5e1
Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78
Inputs (dict keys, declared order) and generated parameter names:
'beta_user' -> input_beta_user
'internal' -> input_internal
'flag_on' -> input_flag_on
'kill_switch' -> input_kill_switch
Outputs (declared order) and their functions:
'enabled' -> output_enabled(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({'beta_user': False, 'internal': False, 'flag_on': False, 'kill_switch': False})
# -> {'enabled': False}
model.output_enabled({'beta_user': False, 'internal': False, 'flag_on': False, 'kill_switch': False})
# -> False
model.evaluate({'beta_user': 1, 'internal': False, 'flag_on': False, 'kill_switch': 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_enabled",
]
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": "e38bc7c67f8a857345783c8ad32faa5a9e83e9828b516a5d2f543e988edde5e1",
"assumptions_digest": "d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78",
"primary_output": "enabled",
"unused_inputs": (),
"subcircuits": (),
}
# Stable ID -> generated identifier (reversible mapping; names are exact, escaped strings).
IDENTIFIER_MAP = {
"v_b5969b9da187": {"kind": "input", "name": "beta_user", "identifier": "input_beta_user"},
"v_8378caade4d3": {"kind": "input", "name": "internal", "identifier": "input_internal"},
"v_087e340e1d25": {"kind": "input", "name": "flag_on", "identifier": "input_flag_on"},
"v_fe3edc05673c": {"kind": "input", "name": "kill_switch", "identifier": "input_kill_switch"},
"f_33a09602b286": {"kind": "output", "name": "enabled", "identifier": "output_enabled"},
}
INPUT_NAMES = ("beta_user", "internal", "flag_on", "kill_switch")
OUTPUT_NAMES = ("enabled",)
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_enabled(input_beta_user: bool, input_internal: bool, input_flag_on: bool, input_kill_switch: bool) -> bool:
"""Decision output 'enabled': (beta_user OR internal) AND flag_on AND NOT kill_switch"""
return (input_beta_user or input_internal) and input_flag_on and (not input_kill_switch)
# ---- Public API ----
def output_enabled(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
"""Decision output 'enabled' (stable ID f_33a09602b286).
'enabled' := (beta_user OR internal) AND flag_on AND NOT kill_switch
Required inputs: 'beta_user', 'internal', 'flag_on', 'kill_switch'.
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, ("beta_user", "internal", "flag_on", "kill_switch"), check_scope)
if check_scope:
_require_in_scope(values)
output_enabled_value = _compute_output_enabled(values["beta_user"], values["internal"], values["flag_on"], values["kill_switch"])
return output_enabled_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: 'beta_user', 'internal', 'flag_on', 'kill_switch'.
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, ("beta_user", "internal", "flag_on", "kill_switch"), check_scope)
if check_scope:
_require_in_scope(values)
output_enabled_value = _compute_output_enabled(values["beta_user"], values["internal"], values["flag_on"], values["kill_switch"])
return {
"enabled": output_enabled_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: e38bc7c67f8a857345783c8ad32faa5a9e83e9828b516a5d2f543e988edde5e1
-- 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_b5969b9da187: beta_user -> "in_beta_user"
-- v_8378caade4d3: internal -> "in_internal"
-- v_087e340e1d25: flag_on -> "in_flag_on"
-- v_fe3edc05673c: kill_switch -> "in_kill_switch"
-- Output columns:
-- f_33a09602b286: enabled -> "out_enabled"
-- 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_enabled] output enabled (stable ID f_33a09602b286)
-- enabled := (beta_user OR internal) AND flag_on AND NOT kill_switch
-- PRECONDITION: "in_beta_user", "in_internal", "in_flag_on", "in_kill_switch" are non-NULL booleans.
-- (("in_beta_user" OR "in_internal") AND "in_flag_on" AND (NOT "in_kill_switch"))
--
-- ----------------------------------------------------------------------------------------------
-- 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_beta_user", "in_internal", "in_flag_on", "in_kill_switch") 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_beta_user" IS NULL OR "in_internal" IS NULL OR "in_flag_on" IS NULL OR "in_kill_switch" IS NULL THEN 'invalid_input'
ELSE 'ok'
END AS "status"
FROM inputs
)
SELECT
"row_id",
"in_beta_user",
"in_internal",
"in_flag_on",
"in_kill_switch",
"status",
CASE WHEN "status" = 'ok' THEN (("in_beta_user" OR "in_internal") AND "in_flag_on" AND (NOT "in_kill_switch")) END AS "out_enabled"
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: e38bc7c67f8a857345783c8ad32faa5a9e83e9828b516a5d2f543e988edde5e1 ; 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_b5969b9da187: beta_user -> in_beta_user ; v_8378caade4d3: internal -> in_internal ; v_087e340e1d25: flag_on -> in_flag_on ; v_fe3edc05673c: kill_switch -> in_kill_switch ; f_33a09602b286: enabled -> out_enabled (set-option :produce-models true) (set-info :smt-lib-version 2.6) (set-logic QF_UF) ; ---- Inputs (declared order) (declare-const in_beta_user Bool) ; beta_user (declare-const in_internal Bool) ; internal (declare-const in_flag_on Bool) ; flag_on (declare-const in_kill_switch Bool) ; kill_switch ; ---- Outputs (dependencies first) ; output enabled (stable ID f_33a09602b286): (beta_user OR internal) AND flag_on AND NOT kill_switch (define-fun out_enabled () Bool (and (or in_beta_user in_internal) in_flag_on (not in_kill_switch))) ; ---- 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
enabled = \left(\mathit{beta\_user} + \mathit{internal}\right) \cdot \mathit{flag\_on} \cdot \overline{\mathit{kill\_switch}}El error habitual
Meter el interruptor de emergencia dentro del grupo de audiencia: (beta_user OR internal AND NOT kill_switch) AND flag_on, de modo que los usuarios beta se lo saltan. La regla prevista tiene tres filas verdaderas, todas con el interruptor apagado; el error añade filas con el interruptor encendido, y el comprobador de equivalencia las listaría.
Preguntas
¿Por qué la FND repite flag_on AND NOT kill_switch en los dos términos?
La distributividad copia las condiciones compartidas en cada término de audiencia, que es como debe escribirse una suma de productos. Los dos términos son los dos grupos de Karnaugh, solapados en la celda 14 donde se aplican las dos audiencias. La original factorizada es más corta de leer; la FND es la lista de perfiles que activan.
Relacionado
Operadores y compuertas
- Compuerta NOT (inversor): tabla de verdad, símbolo y el operador NOT
- Compuerta AND (puerta Y): tabla de verdad de 2, 3 y 4 entradas, símbolo y expresión
- Compuerta OR (puerta O): tabla de verdad de 2, 3 y 4 entradas
Herramientas
- Generador de tablas de verdad: cualquier expresión booleana, hasta 12 variables, con columnas intermedias
- Calculadora y simplificador de álgebra de Boole paso a paso (cada ley nombrada y verificada)
- Solucionador de mapas de Karnaugh: de 2 a 4 variables, agrupaciones, SOP y POS
Véase también
- Lógica de feature flags: combinar flags sin sorpresas
- El error de la regla de entrada: socio OR (invitado AND NOT vetado) y el caso que difiere
- Regla de control de acceso: propietario OR admin OR (editor AND NOT bloqueado)
- Generador de tablas de verdad: cualquier expresión booleana, hasta 12 variables, con columnas intermedias
- Derivar casos de prueba de una tabla de verdad sin probar todas las filas
- Operadores lógicos en JavaScript: &&, ||, !, truthiness y precedencia
Ejemplos resueltos
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