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Traffic-light safety property: never both greens, checked as “always true”

A safety property for a traffic light: ns_go and ew_go are each defined to exclude the other, and the formula conflict, their AND, is checked. The contradiction check holds on all four rows, so the two greens can never be on together.

The model has two inputs, ns_green and ew_green, and three outputs. ns_go is ns_green AND NOT ew_green, ew_go is ew_green AND NOT ns_green, and conflict is ns_go AND ew_go, referring to the first two by name. The property “never both greens” is the statement that conflict is false on every row. The engine's reading of conflict says it is true exactly when both ns_go and ew_go are true. On the four-row table ns_go is true only on row 2, ew_go only on row 1, and conflict on none.

The contradiction check holds: conflict is false on every assignment. Satisfiability is violated, conflict can never be true, and the tautology check is violated with the counterexample of both inputs FALSE. The simplifier found no law to apply to the single AND of two named formulas. The normal-form converter expands the references, two reference-expansion steps, and the complement law reduces both the CNF and the DNF to FALSE. The Karnaugh map draws no groups, zero prime implicants, and derives FALSE; the minterm list is empty and the maxterm list is ΠM(0, 1, 2, 3). Gates for the original: 23 NAND, 11 NOR.

This is how a safety property is checked with a decision model: state the bad event as a formula and ask whether it is a contradiction. The same move works for interlocks, for mutually exclusive states in a UI and for invariants in a configuration. The thing to watch is where the safety comes from. Here conflict is impossible because each go signal is defined with the other's negation; the raw inputs ns_green and ew_green can both be true on row 3. If the controller ever drove the lamps from the inputs instead of the go signals, the property would need re-checking.

ns_go := ns_green AND NOT ew_green · outputew_go := ew_green AND NOT ns_green · outputconflict := ns_go AND ew_go · output

Exact checks

Always true (tautology)? No Counterexample: ns_green = F, ew_green = F · Exhaustively checked and solver cross-checked · 1 rows
Always false (contradiction)? Yes · Exhaustively checked and solver cross-checked · 4 rows
Can be true? No · Exhaustively checked and solver cross-checked · 4 rows

Truth table (4 rows)

Traffic-light safety property: never both greens, checked as “always true”
#ns_greenew_greenns_goew_goconflict
0FALSEFALSEFALSEFALSEFALSE
1FALSETRUEFALSETRUEFALSE
2TRUEFALSETRUEFALSEFALSE
3TRUETRUEFALSEFALSEFALSE

Plain-language reading

Beginnerconflict is true exactly when both ns_go and ew_go are true.
In every other case, conflict is false.
About the operators:
- AND is true only when all of its parts are true.
- A named output used inside a formula stands for that output’s own definition.
Intermediateconflict is true exactly when both ns_go and ew_go are true.
In every other case, conflict is false.
Advancedconflict is true exactly when both ns_go and ew_go are true [conjunction ∧].
In every other case, conflict is false.
Formal notation: ns_go ∧ ew_go

Logic diagram

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

Simplification, step by step

The engine found no law that shortens this expression; it is already as short as its rewriting laws can make it.

ns_go AND ew_go

Karnaugh map

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

Minterms and maxterms

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

Variable order: ns_green, ew_green · 4 rows

Normal forms

Conjunctive normal form (CNF)

FALSE

1 clauses, 0 literals · complete · Reference expansion ×2, Complement ×1

Disjunctive normal form (DNF)

FALSE

0 terms, 0 literals · complete · Reference expansion ×2, Complement ×1

NAND-only and NOR-only

NAND-only form

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 gates · verified equivalent on every row

NOR-only form

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 gates · verified equivalent on every row

The same rule as code

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}

The common slip

Reading the holds verdict on the contradiction check as “the lights are safe”. It says the formula conflict is unsatisfiable, which is exactly right for the go signals as defined. Row 3 of the table, ns_green = TRUE, ew_green = TRUE, shows the inputs themselves are not constrained; the safety is in the definitions.

Questions

Why is the property checked as a contradiction rather than a tautology?

“Never both” is the negation of a bad event, so the natural formula is the bad event and the natural check is that it is always false. Checking NOT conflict as a tautology would give the same information; the page keeps the bad event visible because that is what a reviewer wants to see is impossible.

What does reference expansion do here?

conflict refers to ns_go and ew_go by name. The converter substitutes their definitions, two steps, obtaining ns_green AND NOT ew_green AND ew_green AND NOT ns_green, and the complement law collapses the pair ew_green AND NOT ew_green to FALSE. The step list on the page names each law.

Related

Operators and gates

Tools

See also

Worked examples

Generated from the Tangibool engine, semantics tangibool-semantics/1, engine 1.0.0, build . Every table, map, simplification and verdict on these pages was computed by the Tangibool engine when the site was built, and every claim was re-checked by the same exact checker the app uses. Limits are stated where they apply. © 2026 Foreranger LTD.