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Propiedad de seguridad de un semáforo: nunca dos verdes, comprobada como «siempre verdadera»

Una propiedad de seguridad de un semáforo: ns_go y ew_go se definen excluyéndose mutuamente, y se comprueba conflict, su AND. La contradicción se cumple en las cuatro filas: los dos verdes nunca están encendidos a la vez.

El modelo tiene dos entradas, ns_green y ew_green, y tres salidas. ns_go es ns_green AND NOT ew_green, ew_go es ew_green AND NOT ns_green, y conflict es ns_go AND ew_go, que se refiere a las dos primeras por su nombre. La propiedad «nunca los dos verdes» es la afirmación de que conflict es falso en todas las filas. La lectura del motor de conflict dice que es verdadero exactamente cuando ns_go y ew_go son ambos verdaderos. En la tabla de cuatro filas ns_go es verdadero solo en la fila 2, ew_go solo en la fila 1, y conflict en ninguna.

La contradicción se cumple: conflict es falso en todas las asignaciones. La satisfacibilidad se viola, conflict nunca puede ser verdadero, y la tautología se viola con las dos entradas en FALSO. El simplificador no encontró ninguna ley aplicable al único AND de dos fórmulas con nombre. El conversor desarrolla las referencias, dos pasos, y la ley del complemento reduce la FNC y la FND a FALSE. El mapa no dibuja grupos, cero implicantes primos, y deriva FALSE; la lista de mintérminos está vacía y la de maxtérminos es ΠM(0, 1, 2, 3). Compuertas: 23 NAND, 11 NOR.

Así se comprueba una propiedad de seguridad con un modelo de decisión: se enuncia el suceso malo como fórmula y se pregunta si es una contradicción. El mismo movimiento sirve para enclavamientos, para estados mutuamente excluyentes en una interfaz y para invariantes de una configuración. Vigila de dónde sale la seguridad. Aquí conflict es imposible porque cada señal de paso se define con la negación de la otra; las entradas ns_green y ew_green pueden ser las dos verdaderas en la fila 3. Si el controlador gobernara las lámparas desde las entradas y no desde las señales de paso, habría que volver a comprobar la propiedad.

ns_go := ns_green AND NOT ew_green · salidaew_go := ew_green AND NOT ns_green · salidaconflict := ns_go AND ew_go · salida

Comprobaciones exactas

¿Siempre verdadera (tautología)? No Contraejemplo: ns_green = F, ew_green = F · Exhaustively checked and solver cross-checked · 1 filas
¿Siempre falsa (contradicción)? Sí · Exhaustively checked and solver cross-checked · 4 filas
¿Puede ser verdadera? No · Exhaustively checked and solver cross-checked · 4 filas

Tabla de verdad (4 filas)

Propiedad de seguridad de un semáforo: nunca dos verdes, comprobada como «siempre verdadera»
#ns_greenew_greenns_goew_goconflict
0FALSOFALSOFALSOFALSOFALSO
1FALSOVERDADEROFALSOVERDADEROFALSO
2VERDADEROFALSOVERDADEROFALSOFALSO
3VERDADEROVERDADEROFALSOFALSOFALSO

Lectura en lenguaje claro

Principianteconflict es verdadero exactamente cuando ns_go y ew_go son ambos verdaderos.
En todos los demás casos, conflict es falso.
Sobre los operadores:
- AND (Y) solo es verdadero cuando todas sus partes son verdaderas.
- Una salida con nombre usada dentro de una fórmula representa su propia definición.
Intermedioconflict es verdadero exactamente cuando ns_go y ew_go son ambos verdaderos.
En todos los demás casos, conflict es falso.
Avanzadoconflict es verdadero exactamente cuando ns_go y ew_go son ambos verdaderos [conjunción ∧].
En todos los demás casos, conflict es falso.
Notación formal: ns_go ∧ ew_go

Diagrama lógico

Traffic-light safety property: never both greens, checked as “always true” Traffic-light safety property: never both greens, checked as “always true” ns_green ew_green ns_goPRIMARY ew_go conflict AND NOT AND NOT AND
Traffic-light safety property: never both greens, checked as “always true” Traffic-light safety property: never both greens, checked as “always true” ns_green ew_green ns_goPRIMARY ew_go conflict AND NOT AND NOT 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.

ns_go AND ew_go

Mapa de Karnaugh

ns_green \ ew_green
0
1
0
0m0
0m1
1
0m2
0m3
FALSE · Derived FALSE. Exactly equivalent on every assignment.

Mintérminos y maxtérminos

conflict(ns_green, ew_green) = Σm()conflict(ns_green, ew_green) = ΠM(0, 1, 2, 3)

Orden de variables: ns_green, ew_green · 4 filas

Formas normales

Forma normal conjuntiva (FNC)

FALSE

1 cláusulas, 0 literales · complete · Expansión de una referencia ×2, Complemento ×1

Forma normal disyuntiva (FND)

FALSE

0 términos, 0 literales · complete · Expansión de una referencia ×2, Complemento ×1

Solo NAND, solo NOR

Forma solo con NAND

NAND(NAND(NAND(NAND(ns_green, NAND(ew_green, ew_green)), NAND(ns_green, NAND(ew_green, ew_green))), NAND(NAND(ew_green, NAND(ns_green, ns_green)), NAND(ew_green, NAND(ns_green, ns_green)))), NAND(NAND(NAND(ns_green, NAND(ew_green, ew_green)), NAND(ns_green, NAND(ew_green, ew_green))), NAND(NAND(ew_green, NAND(ns_green, ns_green)), NAND(ew_green, NAND(ns_green, ns_green)))))

23 compuertas · equivalencia verificada en todas las filas

Forma solo con NOR

NOR(NOR(NOR(NOR(ns_green, ns_green), ew_green), NOR(NOR(ns_green, ns_green), ew_green)), NOR(NOR(NOR(ew_green, ew_green), ns_green), NOR(NOR(ew_green, ew_green), ns_green)))

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: fa408e9369f2c9a12a9907ddd7e7940e4933273ead0218609e6a37a78c743d7d
Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78

Inputs (dict keys, declared order) and generated parameter names:
    'ns_green' -> input_ns_green
    'ew_green' -> input_ew_green

Outputs (declared order) and their functions:
    'ns_go' -> output_ns_go(inputs)
    'ew_go' -> output_ew_go(inputs)
    'conflict' -> output_conflict(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({'ns_green': False, 'ew_green': False})
    # -> {'ns_go': False, 'ew_go': False, 'conflict': False}
    model.output_ns_go({'ns_green': False, 'ew_green': False})
    # -> False
    model.evaluate({'ns_green': 1, 'ew_green': 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_ns_go",
    "output_ew_go",
    "output_conflict",
]

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": "fa408e9369f2c9a12a9907ddd7e7940e4933273ead0218609e6a37a78c743d7d",
    "assumptions_digest": "d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78",
    "primary_output": "ns_go",
    "unused_inputs": (),
    "subcircuits": (),
}

# Stable ID -> generated identifier (reversible mapping; names are exact, escaped strings).
IDENTIFIER_MAP = {
    "v_5fbd0000f793": {"kind": "input", "name": "ns_green", "identifier": "input_ns_green"},
    "v_c2f8024e6631": {"kind": "input", "name": "ew_green", "identifier": "input_ew_green"},
    "f_9cfc44c0e181": {"kind": "output", "name": "ns_go", "identifier": "output_ns_go"},
    "f_2f9549d42217": {"kind": "output", "name": "ew_go", "identifier": "output_ew_go"},
    "f_88c1e1772438": {"kind": "output", "name": "conflict", "identifier": "output_conflict"},
}

INPUT_NAMES = ("ns_green", "ew_green")
OUTPUT_NAMES = ("ns_go", "ew_go", "conflict")
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_ns_go(input_ns_green: bool, input_ew_green: bool) -> bool:
    """Decision output 'ns_go': ns_green AND NOT ew_green"""
    return input_ns_green and (not input_ew_green)


def _compute_output_ew_go(input_ns_green: bool, input_ew_green: bool) -> bool:
    """Decision output 'ew_go': ew_green AND NOT ns_green"""
    return input_ew_green and (not input_ns_green)


def _compute_output_conflict(output_ns_go_value: bool, output_ew_go_value: bool) -> bool:
    """Decision output 'conflict': ns_go AND ew_go (references are passed in once computed: 'ns_go' -> output_ns_go_value, 'ew_go' -> output_ew_go_value)"""
    return output_ns_go_value and output_ew_go_value


# ---- Public API ----


def output_ns_go(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'ns_go' (stable ID f_9cfc44c0e181).

    'ns_go' := ns_green AND NOT ew_green

    Required inputs: 'ns_green', 'ew_green'.
    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, ("ns_green", "ew_green"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_ns_go_value = _compute_output_ns_go(values["ns_green"], values["ew_green"])
    return output_ns_go_value


def output_ew_go(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'ew_go' (stable ID f_2f9549d42217).

    'ew_go' := ew_green AND NOT ns_green

    Required inputs: 'ns_green', 'ew_green'.
    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, ("ns_green", "ew_green"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_ew_go_value = _compute_output_ew_go(values["ns_green"], values["ew_green"])
    return output_ew_go_value


def output_conflict(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'conflict' (stable ID f_88c1e1772438).

    'conflict' := ns_go AND ew_go

    Required inputs: 'ns_green', 'ew_green'.
    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, ("ns_green", "ew_green"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_ns_go_value = _compute_output_ns_go(values["ns_green"], values["ew_green"])
    output_ew_go_value = _compute_output_ew_go(values["ns_green"], values["ew_green"])
    output_conflict_value = _compute_output_conflict(output_ns_go_value, output_ew_go_value)
    return output_conflict_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: 'ns_green', 'ew_green'.
    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, ("ns_green", "ew_green"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_ns_go_value = _compute_output_ns_go(values["ns_green"], values["ew_green"])
    output_ew_go_value = _compute_output_ew_go(values["ns_green"], values["ew_green"])
    output_conflict_value = _compute_output_conflict(output_ns_go_value, output_ew_go_value)
    return {
        "ns_go": output_ns_go_value,
        "ew_go": output_ew_go_value,
        "conflict": output_conflict_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: fa408e9369f2c9a12a9907ddd7e7940e4933273ead0218609e6a37a78c743d7d
-- 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_5fbd0000f793: ns_green -> "in_ns_green"
--   v_c2f8024e6631: ew_green -> "in_ew_green"
-- Output columns:
--   f_9cfc44c0e181: ns_go -> "out_ns_go"
--   f_2f9549d42217: ew_go -> "out_ew_go"
--   f_88c1e1772438: conflict -> "out_conflict"
-- Assumptions (scope K; exported separately and never folded into an output):
--   none; every complete input row is in scope.
-- Named-output references are expanded in place.

-- ----------------------------------------------------------------------------------------------
-- 1. Expression fragments (parenthesised; non-NULL boolean inputs required)
-- ----------------------------------------------------------------------------------------------
--
-- [out_ns_go] output ns_go (stable ID f_9cfc44c0e181)
--   ns_go := ns_green AND NOT ew_green
--   PRECONDITION: "in_ns_green", "in_ew_green" are non-NULL booleans.
--   ("in_ns_green" AND (NOT "in_ew_green"))
--
-- [out_ew_go] output ew_go (stable ID f_2f9549d42217)
--   ew_go := ew_green AND NOT ns_green
--   PRECONDITION: "in_ns_green", "in_ew_green" are non-NULL booleans.
--   ("in_ew_green" AND (NOT "in_ns_green"))
--
-- [out_conflict] output conflict (stable ID f_88c1e1772438)
--   conflict := ns_go AND ew_go
--   PRECONDITION: "in_ns_green", "in_ew_green" are non-NULL booleans.
--   (("in_ns_green" AND (NOT "in_ew_green")) AND ("in_ew_green" AND (NOT "in_ns_green")))
--

-- ----------------------------------------------------------------------------------------------
-- 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_ns_green", "in_ew_green") 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_ns_green" IS NULL OR "in_ew_green" IS NULL THEN 'invalid_input'
      ELSE 'ok'
    END AS "status"
  FROM inputs
)
SELECT
  "row_id",
  "in_ns_green",
  "in_ew_green",
  "status",
  CASE WHEN "status" = 'ok' THEN ("in_ns_green" AND (NOT "in_ew_green")) END AS "out_ns_go",
  CASE WHEN "status" = 'ok' THEN ("in_ew_green" AND (NOT "in_ns_green")) END AS "out_ew_go",
  CASE WHEN "status" = 'ok' THEN (("in_ns_green" AND (NOT "in_ew_green")) AND ("in_ew_green" AND (NOT "in_ns_green"))) END AS "out_conflict"
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: fa408e9369f2c9a12a9907ddd7e7940e4933273ead0218609e6a37a78c743d7d
; 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_5fbd0000f793: ns_green -> in_ns_green
;   v_c2f8024e6631: ew_green -> in_ew_green
;   f_9cfc44c0e181: ns_go -> out_ns_go
;   f_2f9549d42217: ew_go -> out_ew_go
;   f_88c1e1772438: conflict -> out_conflict

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

; ---- Inputs (declared order)
(declare-const in_ns_green Bool) ; ns_green
(declare-const in_ew_green Bool) ; ew_green

; ---- Outputs (dependencies first)
; output ns_go (stable ID f_9cfc44c0e181): ns_green AND NOT ew_green
(define-fun out_ns_go () Bool (and in_ns_green (not in_ew_green)))
; output ew_go (stable ID f_2f9549d42217): ew_green AND NOT ns_green
(define-fun out_ew_go () Bool (and in_ew_green (not in_ns_green)))
; output conflict (stable ID f_88c1e1772438): ns_go AND ew_go
(define-fun out_conflict () Bool (and out_ns_go out_ew_go))

; ---- 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
ns_go = \mathit{ns\_green} \cdot \overline{\mathit{ew\_green}}
ew_go = \mathit{ew\_green} \cdot \overline{\mathit{ns\_green}}
conflict = \mathit{ns\_go} \cdot \mathit{ew\_go}

El error habitual

Leer el «se cumple» de la contradicción como «el semáforo es seguro». Dice que conflict es insatisfacible, lo correcto para las señales de paso tal como están definidas. La fila 3, ns_green = VERDADERO, ew_green = VERDADERO, muestra que las entradas no están restringidas; la seguridad está en las definiciones.

Preguntas

¿Por qué la propiedad se comprueba como contradicción y no como tautología?

«Nunca los dos» es la negación de un suceso malo, así que la fórmula natural es el suceso malo y la comprobación natural es que sea siempre falso. Comprobar NOT conflict como tautología daría la misma información; la página mantiene visible el suceso malo porque eso es lo que quien revisa quiere ver que es imposible.

¿Qué hace aquí el desarrollo de referencias?

conflict se refiere a ns_go y ew_go por su nombre. El conversor sustituye sus definiciones, dos pasos, y obtiene ns_green AND NOT ew_green AND ew_green AND NOT ns_green, y la ley del complemento contrae el par ew_green AND NOT ew_green a FALSE. La lista de pasos de la página nombra cada ley.

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.