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Two-bit equality: (A1 XNOR B1) AND (A0 XNOR B0)

Two-bit equality, XNOR(A1, B1) AND XNOR(A0, B0): both bit pairs must match. Sixteen rows with four true ones, an eight-literal CNF against a sixteen-literal DNF, and a map where no two ones touch.

Two two-bit numbers are equal when their high bits match and their low bits match. XNOR is the one-bit equality test, so the formula ANDs two of them. The engine's reading says equal holds exactly when A1 and B1 have the same value and A0 and B0 have the same value. With four inputs the table has sixteen rows, and the output is true on four of them, Σm(0, 3, 12, 15): 00 = 00, 01 = 01, 10 = 10 and 11 = 11.

The tautology check is violated with the counterexample A1 = FALSE, B1 = FALSE, A0 = FALSE, B0 = TRUE; satisfiability holds with the witness of all four inputs FALSE. The simplifier found no law that shortens the three-operator expression. The normal forms differ sharply in size: the CNF, by XNOR elimination twice, is (A1 OR NOT B1) AND (NOT A1 OR B1) AND (A0 OR NOT B0) AND (NOT A0 OR B0), eight literals; the DNF needs a distribution step too and has four terms of four literals, sixteen in all. The Karnaugh map draws four one-cell groups, four prime implicants. Gate counts: 47 NAND, 23 NOR.

Equality comparators sit in every processor's branch unit and every cache's tag match, and the structure scales by adding one XNOR per bit under the AND. In software the same thing is a field-by-field equals method. The thing to watch is the size asymmetry: the product-of-sums form stays small because equality is a conjunction of small tests, while the sum-of-products form has to enumerate every matching pair of values. Choose the form that matches the structure of the question.

equal := XNOR(A1, B1) AND XNOR(A0, B0) · output

Exact checks

Always true (tautology)? No Counterexample: A1 = F, B1 = F, A0 = F, B0 = T · Exhaustively checked and solver cross-checked · 2 rows
Always false (contradiction)? No Counterexample: A1 = F, B1 = F, A0 = F, B0 = F · Exhaustively checked and solver cross-checked · 1 rows
Can be true? Yes Example assignment: A1 = F, B1 = F, A0 = F, B0 = F · Exhaustively checked and solver cross-checked · 1 rows

Truth table (16 rows)

Two-bit equality: (A1 XNOR B1) AND (A0 XNOR B0)
#A1B1A0B0equal
0FALSEFALSEFALSEFALSETRUE
1FALSEFALSEFALSETRUEFALSE
2FALSEFALSETRUEFALSEFALSE
3FALSEFALSETRUETRUETRUE
4FALSETRUEFALSEFALSEFALSE
5FALSETRUEFALSETRUEFALSE
6FALSETRUETRUEFALSEFALSE
7FALSETRUETRUETRUEFALSE
8TRUEFALSEFALSEFALSEFALSE
9TRUEFALSEFALSETRUEFALSE
10TRUEFALSETRUEFALSEFALSE
11TRUEFALSETRUETRUEFALSE
12TRUETRUEFALSEFALSETRUE
13TRUETRUEFALSETRUEFALSE
14TRUETRUETRUEFALSEFALSE
15TRUETRUETRUETRUETRUE

Plain-language reading

Beginnerequal is true exactly when both of the following hold:
1. A1 and B1 have the same value (both true or both false)
2. A0 and B0 have the same value (both true or both false)
In every other case, equal is false.
About the operators:
- AND is true only when all of its parts are true.
- XNOR is true when both parts have the same value.
Intermediateequal is true exactly when both of the following hold:
1. A1 and B1 have the same value (both true or both false)
2. A0 and B0 have the same value (both true or both false)
In every other case, equal is false.
Advancedequal is true exactly when both of the following hold [conjunction ∧]:
1. A1 and B1 have the same value (both true or both false) [equivalence gate (XNOR)]
2. A0 and B0 have the same value (both true or both false) [equivalence gate (XNOR)]
In every other case, equal is false.
Formal notation: XNOR(A1, B1) ∧ XNOR(A0, B0)

Logic diagram

Two-bit equality: (A1 XNOR B1) AND (A0 XNOR B0) Two-bit equality: (A1 XNOR B1) AND (A0 XNOR B0) A1 B1 A0 B0 equal AND XNOR XNOR
Two-bit equality: (A1 XNOR B1) AND (A0 XNOR B0) Two-bit equality: (A1 XNOR B1) AND (A0 XNOR B0) A1 B1 A0 B0 equal AND XNOR XNOR

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.

XNOR(A1, B1) AND XNOR(A0, B0)

Karnaugh map

A1B1 \ A0B0
00
01
11
10
00
1m0
0m1
1m3
0m2
01
0m4
0m5
0m7
0m6
11
1m12
0m13
1m15
0m14
10
0m8
0m9
0m11
0m10
  1. cells m0NOT A1 AND NOT B1 AND NOT A0 AND NOT B0
  2. cells m3NOT A1 AND NOT B1 AND A0 AND B0
  3. cells m12A1 AND B1 AND NOT A0 AND NOT B0
  4. cells m15A1 AND B1 AND A0 AND B0
(NOT A1 AND NOT B1 AND NOT A0 AND NOT B0) OR (NOT A1 AND NOT B1 AND A0 AND B0) OR (A1 AND B1 AND NOT A0 AND NOT B0) OR (A1 AND B1 AND A0 AND B0) · Derived (NOT A1 AND NOT B1 AND NOT A0 AND NOT B0) OR (NOT A1 AND NOT B1 AND A0 AND B0) OR (A1 AND B1 AND NOT A0 AND NOT B0) OR (A1 AND B1 AND A0 AND B0). Exactly equivalent on every assignment.

Minterms and maxterms

equal(A1, B1, A0, B0) = Σm(0, 3, 12, 15)equal(A1, B1, A0, B0) = ΠM(1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14)

Variable order: A1, B1, A0, B0 · 16 rows

Normal forms

Conjunctive normal form (CNF)

(A1 OR NOT B1) AND (NOT A1 OR B1) AND (A0 OR NOT B0) AND (NOT A0 OR B0)

4 clauses, 8 literals · complete · XNOR elimination ×2

Disjunctive normal form (DNF)

(A1 AND B1 AND A0 AND B0) OR (A1 AND B1 AND NOT A0 AND NOT B0) OR (NOT A1 AND NOT B1 AND A0 AND B0) OR (NOT A1 AND NOT B1 AND NOT A0 AND NOT B0)

4 terms, 16 literals · complete · XNOR elimination ×2, Distribution ×1

NAND-only and NOR-only

NAND-only form

NAND(NAND(NAND(NAND(NAND(A1, NAND(B1, B1)), NAND(NAND(A1, A1), B1)), NAND(NAND(A1, NAND(B1, B1)), NAND(NAND(A1, A1), B1))), NAND(NAND(NAND(A0, NAND(B0, B0)), NAND(NAND(A0, A0), B0)), NAND(NAND(A0, NAND(B0, B0)), NAND(NAND(A0, A0), B0)))), NAND(NAND(NAND(NAND(A1, NAND(B1, B1)), NAND(NAND(A1, A1), B1)), NAND(NAND(A1, NAND(B1, B1)), NAND(NAND(A1, A1), B1))), NAND(NAND(NAND(A0, NAND(B0, B0)), NAND(NAND(A0, A0), B0)), NAND(NAND(A0, NAND(B0, B0)), NAND(NAND(A0, A0), B0)))))

47 gates · verified equivalent on every row

NOR-only form

NOR(NOR(NOR(NOR(NOR(A1, A1), B1), NOR(A1, NOR(B1, B1))), NOR(NOR(NOR(A1, A1), B1), NOR(A1, NOR(B1, B1)))), NOR(NOR(NOR(NOR(A0, A0), B0), NOR(A0, NOR(B0, B0))), NOR(NOR(NOR(A0, A0), B0), NOR(A0, NOR(B0, B0)))))

23 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: 80541868ec70b6db7650faa5f60a35cdc3317f7c52006b01250ed71dae57989c
Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78

Inputs (dict keys, declared order) and generated parameter names:
    'A1' -> input_A1
    'B1' -> input_B1
    'A0' -> input_A0
    'B0' -> input_B0

Outputs (declared order) and their functions:
    'equal' -> output_equal(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({'A1': False, 'B1': False, 'A0': False, 'B0': False})
    # -> {'equal': True}
    model.output_equal({'A1': False, 'B1': False, 'A0': False, 'B0': False})
    # -> True
    model.evaluate({'A1': 1, 'B1': False, 'A0': False, 'B0': 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_equal",
]

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": "80541868ec70b6db7650faa5f60a35cdc3317f7c52006b01250ed71dae57989c",
    "assumptions_digest": "d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78",
    "primary_output": "equal",
    "unused_inputs": (),
    "subcircuits": (),
}

# Stable ID -> generated identifier (reversible mapping; names are exact, escaped strings).
IDENTIFIER_MAP = {
    "v_b85aa55232f9": {"kind": "input", "name": "A1", "identifier": "input_A1"},
    "v_642166f389e0": {"kind": "input", "name": "B1", "identifier": "input_B1"},
    "v_022e27020ecc": {"kind": "input", "name": "A0", "identifier": "input_A0"},
    "v_83a0c82dd0b4": {"kind": "input", "name": "B0", "identifier": "input_B0"},
    "f_e0aba2c1efc2": {"kind": "output", "name": "equal", "identifier": "output_equal"},
}

INPUT_NAMES = ("A1", "B1", "A0", "B0")
OUTPUT_NAMES = ("equal",)
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_equal(input_A1: bool, input_B1: bool, input_A0: bool, input_B0: bool) -> bool:
    """Decision output 'equal': XNOR(A1, B1) AND XNOR(A0, B0)"""
    return (input_A1 == input_B1) and (input_A0 == input_B0)


# ---- Public API ----


def output_equal(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'equal' (stable ID f_e0aba2c1efc2).

    'equal' := XNOR(A1, B1) AND XNOR(A0, B0)

    Required inputs: 'A1', 'B1', 'A0', 'B0'.
    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, ("A1", "B1", "A0", "B0"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_equal_value = _compute_output_equal(values["A1"], values["B1"], values["A0"], values["B0"])
    return output_equal_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: 'A1', 'B1', 'A0', 'B0'.
    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, ("A1", "B1", "A0", "B0"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_equal_value = _compute_output_equal(values["A1"], values["B1"], values["A0"], values["B0"])
    return {
        "equal": output_equal_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: 80541868ec70b6db7650faa5f60a35cdc3317f7c52006b01250ed71dae57989c
-- 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_b85aa55232f9: A1 -> "in_A1"
--   v_642166f389e0: B1 -> "in_B1"
--   v_022e27020ecc: A0 -> "in_A0"
--   v_83a0c82dd0b4: B0 -> "in_B0"
-- Output columns:
--   f_e0aba2c1efc2: equal -> "out_equal"
-- 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_equal] output equal (stable ID f_e0aba2c1efc2)
--   equal := XNOR(A1, B1) AND XNOR(A0, B0)
--   PRECONDITION: "in_A1", "in_B1", "in_A0", "in_B0" are non-NULL booleans.
--   (("in_A1" = "in_B1") AND ("in_A0" = "in_B0"))
--

-- ----------------------------------------------------------------------------------------------
-- 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_A1", "in_B1", "in_A0", "in_B0") 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_A1" IS NULL OR "in_B1" IS NULL OR "in_A0" IS NULL OR "in_B0" IS NULL THEN 'invalid_input'
      ELSE 'ok'
    END AS "status"
  FROM inputs
)
SELECT
  "row_id",
  "in_A1",
  "in_B1",
  "in_A0",
  "in_B0",
  "status",
  CASE WHEN "status" = 'ok' THEN (("in_A1" = "in_B1") AND ("in_A0" = "in_B0")) END AS "out_equal"
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: 80541868ec70b6db7650faa5f60a35cdc3317f7c52006b01250ed71dae57989c
; 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_b85aa55232f9: A1 -> in_A1
;   v_642166f389e0: B1 -> in_B1
;   v_022e27020ecc: A0 -> in_A0
;   v_83a0c82dd0b4: B0 -> in_B0
;   f_e0aba2c1efc2: equal -> out_equal

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

; ---- Inputs (declared order)
(declare-const in_A1 Bool) ; A1
(declare-const in_B1 Bool) ; B1
(declare-const in_A0 Bool) ; A0
(declare-const in_B0 Bool) ; B0

; ---- Outputs (dependencies first)
; output equal (stable ID f_e0aba2c1efc2): XNOR(A1, B1) AND XNOR(A0, B0)
(define-fun out_equal () Bool (and (= in_A1 in_B1) (= in_A0 in_B0)))

; ---- 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
equal = \overline{\mathit{A1} \oplus \mathit{B1}} \cdot \overline{\mathit{A0} \oplus \mathit{B0}}

The common slip

Building equality from XOR instead of XNOR and forgetting the final inversion. XOR(A1, B1) AND XOR(A0, B0) is true when both bits differ, not when they match; on the table it lights rows such as A1 = FALSE, B1 = TRUE, A0 = FALSE, B0 = TRUE, where the numbers are 0 and 3.

Questions

Why does the DNF have sixteen literals and the CNF only eight?

The CNF is a conjunction of the two XNOR tests, each a pair of two-literal clauses, so it needs no cross-multiplication. The DNF has to distribute the AND over both XNORs and list every combination of matching values, four terms that each name all four inputs.

Related

Operators and gates

Tools

See also

Worked examples

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