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Distribution in practice: A AND (B OR C) expanded

A AND (B OR C) expanded to (A AND B) OR (A AND C) and checked on all eight rows. The factored form is already a CNF, the expanded form is the DNF, and the two gate families prefer opposite sides.

Distribution lets an AND spread over an OR, the way multiplication spreads over addition: A must hold, and at least one of B or C must hold, so either A with B or A with C. The engine's reading of the factored form says factored is true exactly when A is true and at least one of B or C is true. On the eight-row table both formulas are true on rows 5, 6 and 7, Σm(5, 6, 7): A true, and not both of B and C false.

The equivalence check holds: factored and expanded agree on every assignment. Not a tautology, counterexample A = FALSE, B = FALSE, C = FALSE; satisfiable, witness A = TRUE, B = FALSE, C = TRUE. The simplifier found no law that shortens the two-operator expression. The normal forms are the two sides of this page: the CNF converter returns A AND (B OR C) unchanged, and the DNF converter applies distribution once to reach (A AND B) OR (A AND C). The Karnaugh map derives the expanded form from two groups, two prime implicants. Gates: 3 NOR, NOR(NOR(A, A), NOR(B, C)), against 9 NAND.

Distribution is how a rule gets flattened for a database query, where WHERE a AND (b OR c) and the expanded form run the same but may be planned differently, and how a condition gets factored for readability in code. The thing to watch is the literal count: expanding duplicates A, and with more terms the duplication multiplies, which is why the DNF of a larger rule can be much longer than its CNF. Factor when you write for humans; expand when a tool needs sum-of-products.

factored := A AND (B OR C) · outputexpanded := (A AND B) OR (A AND C) · output

Exact checks

Always true (tautology)? No Counterexample: A = F, B = F, C = F · Exhaustively checked and solver cross-checked · 1 rows
Always false (contradiction)? No Counterexample: A = T, B = F, C = T · Exhaustively checked and solver cross-checked · 6 rows
Can be true? Yes Example assignment: A = T, B = F, C = T · Exhaustively checked and solver cross-checked · 6 rows
Are factored and expanded equivalent? Yes · Exhaustively checked and solver cross-checked · 8 rows

Truth table (8 rows)

Distribution in practice: A AND (B OR C) expanded
#ABCfactoredexpanded
0FALSEFALSEFALSEFALSEFALSE
1FALSEFALSETRUEFALSEFALSE
2FALSETRUEFALSEFALSEFALSE
3FALSETRUETRUEFALSEFALSE
4TRUEFALSEFALSEFALSEFALSE
5TRUEFALSETRUETRUETRUE
6TRUETRUEFALSETRUETRUE
7TRUETRUETRUETRUETRUE

Plain-language reading

Beginnerfactored is true exactly when both of the following hold:
1. A is true
2. at least one of B or C is true (both may be true)
In every other case, factored is false.
About the operators:
- AND is true only when all of its parts are true.
- OR is inclusive: it is true when at least one part is true, including when several are.
Intermediatefactored is true exactly when both of the following hold:
1. A is true
2. at least one of B or C is true (both may be true)
In every other case, factored is false.
Advancedfactored is true exactly when both of the following hold [conjunction ∧]:
1. A is true
2. at least one of B or C is true (both may be true) [inclusive disjunction ∨]
In every other case, factored is false.
Formal notation: A ∧ (B ∨ C)

Logic diagram

Distribution in practice: A AND (B OR C) expanded Distribution in practice: A AND (B OR C) expanded A B C factoredPRIMARY expanded AND OR OR AND AND
Distribution in practice: A AND (B OR C) expanded Distribution in practice: A AND (B OR C) expanded A B C factoredPRIMARY expanded AND OR OR AND 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.

A AND (B OR C)

Karnaugh map

A \ BC
00
01
11
10
0
0m0
0m1
0m3
0m2
1
0m4
1m5
1m7
1m6
  1. cells m6, m7A AND B
  2. cells m5, m7A AND C
(A AND B) OR (A AND C) · Derived (A AND B) OR (A AND C). Exactly equivalent on every assignment.

Minterms and maxterms

factored(A, B, C) = Σm(5, 6, 7)factored(A, B, C) = ΠM(0, 1, 2, 3, 4)

Variable order: A, B, C · 8 rows

Normal forms

Conjunctive normal form (CNF)

A AND (B OR C)

2 clauses, 3 literals · complete

Disjunctive normal form (DNF)

(A AND B) OR (A AND C)

2 terms, 4 literals · complete · Distribution ×1

NAND-only and NOR-only

NAND-only form

NAND(NAND(A, NAND(NAND(B, B), NAND(C, C))), NAND(A, NAND(NAND(B, B), NAND(C, C))))

9 gates · verified equivalent on every row

NOR-only form

NOR(NOR(A, A), NOR(B, C))

3 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: fe6b00146acee1aa430190e6fe1181b7e281d9d137b4edab6c4da7b77fdcd354
Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78

Inputs (dict keys, declared order) and generated parameter names:
    'A' -> input_A
    'B' -> input_B
    'C' -> input_C

Outputs (declared order) and their functions:
    'factored' -> output_factored(inputs)
    'expanded' -> output_expanded(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({'A': False, 'B': False, 'C': False})
    # -> {'factored': False, 'expanded': False}
    model.output_factored({'A': False, 'B': False, 'C': False})
    # -> False
    model.evaluate({'A': 1, 'B': False, 'C': 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_factored",
    "output_expanded",
]

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": "fe6b00146acee1aa430190e6fe1181b7e281d9d137b4edab6c4da7b77fdcd354",
    "assumptions_digest": "d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78",
    "primary_output": "factored",
    "unused_inputs": (),
    "subcircuits": (),
}

# Stable ID -> generated identifier (reversible mapping; names are exact, escaped strings).
IDENTIFIER_MAP = {
    "v_c9f4edca5701": {"kind": "input", "name": "A", "identifier": "input_A"},
    "v_df3bbb8877ba": {"kind": "input", "name": "B", "identifier": "input_B"},
    "v_3f70d5977bf0": {"kind": "input", "name": "C", "identifier": "input_C"},
    "f_6fb4bf775421": {"kind": "output", "name": "factored", "identifier": "output_factored"},
    "f_fe27d7bbea53": {"kind": "output", "name": "expanded", "identifier": "output_expanded"},
}

INPUT_NAMES = ("A", "B", "C")
OUTPUT_NAMES = ("factored", "expanded")
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_factored(input_A: bool, input_B: bool, input_C: bool) -> bool:
    """Decision output 'factored': A AND (B OR C)"""
    return input_A and (input_B or input_C)


def _compute_output_expanded(input_A: bool, input_B: bool, input_C: bool) -> bool:
    """Decision output 'expanded': (A AND B) OR (A AND C)"""
    return (input_A and input_B) or (input_A and input_C)


# ---- Public API ----


def output_factored(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'factored' (stable ID f_6fb4bf775421).

    'factored' := A AND (B OR C)

    Required inputs: 'A', 'B', 'C'.
    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, ("A", "B", "C"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_factored_value = _compute_output_factored(values["A"], values["B"], values["C"])
    return output_factored_value


def output_expanded(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
    """Decision output 'expanded' (stable ID f_fe27d7bbea53).

    'expanded' := (A AND B) OR (A AND C)

    Required inputs: 'A', 'B', 'C'.
    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, ("A", "B", "C"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_expanded_value = _compute_output_expanded(values["A"], values["B"], values["C"])
    return output_expanded_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: 'A', 'B', 'C'.
    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, ("A", "B", "C"), check_scope)
    if check_scope:
        _require_in_scope(values)
    output_factored_value = _compute_output_factored(values["A"], values["B"], values["C"])
    output_expanded_value = _compute_output_expanded(values["A"], values["B"], values["C"])
    return {
        "factored": output_factored_value,
        "expanded": output_expanded_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: fe6b00146acee1aa430190e6fe1181b7e281d9d137b4edab6c4da7b77fdcd354
-- 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_c9f4edca5701: A -> "in_A"
--   v_df3bbb8877ba: B -> "in_B"
--   v_3f70d5977bf0: C -> "in_C"
-- Output columns:
--   f_6fb4bf775421: factored -> "out_factored"
--   f_fe27d7bbea53: expanded -> "out_expanded"
-- 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_factored] output factored (stable ID f_6fb4bf775421)
--   factored := A AND (B OR C)
--   PRECONDITION: "in_A", "in_B", "in_C" are non-NULL booleans.
--   ("in_A" AND ("in_B" OR "in_C"))
--
-- [out_expanded] output expanded (stable ID f_fe27d7bbea53)
--   expanded := (A AND B) OR (A AND C)
--   PRECONDITION: "in_A", "in_B", "in_C" are non-NULL booleans.
--   (("in_A" AND "in_B") OR ("in_A" AND "in_C"))
--

-- ----------------------------------------------------------------------------------------------
-- 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_A", "in_B", "in_C") AS (
  -- tangibool:example-rows:begin
  VALUES
    (1, FALSE, FALSE, FALSE),
    (2, FALSE, FALSE, TRUE),
    (3, FALSE, TRUE, FALSE),
    (4, FALSE, TRUE, TRUE),
    (5, TRUE, FALSE, FALSE),
    (6, TRUE, FALSE, TRUE),
    (7, TRUE, TRUE, FALSE),
    (8, TRUE, TRUE, TRUE),
    (9, NULL::boolean, FALSE, FALSE)
  -- tangibool:example-rows:end
),
checked AS (
  SELECT
    inputs.*,
    CASE
      WHEN "in_A" IS NULL OR "in_B" IS NULL OR "in_C" IS NULL THEN 'invalid_input'
      ELSE 'ok'
    END AS "status"
  FROM inputs
)
SELECT
  "row_id",
  "in_A",
  "in_B",
  "in_C",
  "status",
  CASE WHEN "status" = 'ok' THEN ("in_A" AND ("in_B" OR "in_C")) END AS "out_factored",
  CASE WHEN "status" = 'ok' THEN (("in_A" AND "in_B") OR ("in_A" AND "in_C")) END AS "out_expanded"
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: fe6b00146acee1aa430190e6fe1181b7e281d9d137b4edab6c4da7b77fdcd354
; 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_c9f4edca5701: A -> in_A
;   v_df3bbb8877ba: B -> in_B
;   v_3f70d5977bf0: C -> in_C
;   f_6fb4bf775421: factored -> out_factored
;   f_fe27d7bbea53: expanded -> out_expanded

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

; ---- Inputs (declared order)
(declare-const in_A Bool) ; A
(declare-const in_B Bool) ; B
(declare-const in_C Bool) ; C

; ---- Outputs (dependencies first)
; output factored (stable ID f_6fb4bf775421): A AND (B OR C)
(define-fun out_factored () Bool (and in_A (or in_B in_C)))
; output expanded (stable ID f_fe27d7bbea53): (A AND B) OR (A AND C)
(define-fun out_expanded () Bool (or (and in_A in_B) (and in_A in_C)))

; ---- 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
factored = A \cdot \left(B + C\right)
expanded = \left(A \cdot B\right) + \left(A \cdot C\right)

The common slip

Distributing in the wrong direction: A AND (B OR C) is not (A AND B) OR C. Dropping the second A changes the function on rows where C is true and A is false, such as A = FALSE, B = FALSE, C = TRUE. The table shows the factored form false there, and an unbalanced expansion true.

Questions

Does OR also distribute over AND?

Yes: A OR (B AND C) = (A OR B) AND (A OR C), the dual law, which the CNF converter uses whenever it has to turn a sum of products into a product of sums. The distribution law page proves both directions by truth table.

Why does the NOR form favour the factored side?

A AND (B OR C) is an AND with an OR under it, and a NOR of inverted inputs builds the AND while a NOR builds the OR: 3 gates. The NAND family has to invert more signals for this shape, so its mechanical construction needs 9.

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.