A topic in the Open Knowledge Graph — a free, open map of 15,290 topics and the order to learn them in.

Tautologies, Contradictions, and Satisfiability

College Depth 72 in the knowledge graph I know this Set as goal
632topics build on this
324prerequisites beneath it
See this on the map →
Propositional ConnectivesPropositional Semantics and Valuations+3 moreConjunctive and Disjunctive Normal FormsConsistency and Inconsistency of Theories+4 more
tautology contradiction satisfiability validity

Core Idea

A tautology is a formula true under every possible valuation (e.g., p ∨ ¬p); a contradiction is false under every valuation (e.g., p ∧ ¬p); a contingency is neither. A formula is satisfiable if at least one valuation makes it true. These classifications partition the space of propositional formulas and are central to logic — proof systems aim to derive exactly the tautologies. The semantic notion of validity (⊨ φ) is the target that syntactic proof systems strive to match.

How It's Best Learned

Classify a variety of formulas before and after applying De Morgan's laws. Practice converting the question 'is φ a tautology?' to 'is ¬φ a contradiction?' and verify the equivalence.

Common Misconceptions

Explainer

You know from propositional semantics that a formula's truth value depends on a truth assignment — a function mapping each propositional variable to true or false. A formula with n distinct variables has 2ⁿ possible truth assignments. The central classifications of propositional logic ask: what does a formula's truth value look like *across all* those assignments?

A tautology (also called a validity) is true under every possible truth assignment — not some, not most, but all of them. The classic example is p ∨ ¬p ("law of excluded middle"): no matter what truth value p takes, one of p and ¬p is true, so the disjunction is always true. A contradiction (also called an unsatisfiable formula) is false under every assignment. The example p ∧ ¬p assigns p a value, then requires it to be both true and false simultaneously — impossible. A contingency falls in between: true under some assignments, false under others. The formula p → q is contingent: it fails only when p is true and q is false.

The third classification, satisfiability, cuts differently: a formula is satisfiable if at least one truth assignment makes it true. Every tautology is satisfiable (all assignments work); every contradiction is unsatisfiable (no assignment works); contingencies are satisfiable but not tautologies. Satisfiability is the focus of SAT solvers and computational complexity — it is the question "can this formula ever be true?" rather than "is this formula always true?"

The most useful transformation here is one you can derive from the logical equivalences you know: φ is a tautology if and only if ¬φ is a contradiction if and only if ¬φ is unsatisfiable. This equivalence is practically powerful because it lets you convert a tautology-checking question into a satisfiability-checking question (and vice versa), which matters for proof systems and automated reasoning. In a proof system, the goal is to derive exactly the tautologies — the formulas whose negations are unsatisfiable, i.e., the ones no consistent assignment can falsify. The semantic target of proof theory is tautology; satisfiability is the complementary concept used to detect when a formula can coherently be false.

Practice Questions 5 questions

Prerequisite Chain

Understanding ZeroThe Number ZeroCounting to FiveCounting to 10Counting to 20Counting a Set of Objects Up to 20Cardinality: The Last Number CountedMatching Numerals to QuantitiesSubitizing Small QuantitiesAddition Within 10Number Bonds to 10Addition Within 20Doubles and Near DoublesDoubles Facts Within 10Near Doubles Facts Within 20Mental Math Strategies for AdditionMental Math: Adding and Subtracting TensAddition Within 100Repeated Addition as MultiplicationMultiplication as Equal GroupsMultiplication: ArraysBasic Multiplication Facts (0s, 1s, 2s, 5s, 10s)Multiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Multiplication and Division Fact FamiliesRelationship Between Multiplication and DivisionDivision Facts as Inverse of MultiplicationRemainders and Quotients in DivisionDivision Word ProblemsMulti-Step Word ProblemsSolving Multi-Step Word ProblemsMultiplication Word ProblemsDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueIntegers and the Number LineComparing and Ordering IntegersAbsolute ValueAdding IntegersSubtracting IntegersMultiplying IntegersIntroduction to ExponentsOrder of OperationsInteger Order of OperationsVariable ExpressionsThe Distributive PropertyVariables and Expressions ReviewIntroduction to PolynomialsAdding and Subtracting PolynomialsMultiplying PolynomialsFactorialPermutationsCombinationsCounting Principles: Addition and Multiplication RulesIntroduction to Graph TheoryPropositional Logic FoundationsLogical EquivalencesBoolean AlgebraIntroduction to Propositional LogicPropositional ConnectivesTruth Assignments and ValuationsTautologies, Contradictions, and Satisfiability

Longest path: 73 steps · 324 total prerequisite topics

Prerequisites (5)

Leads To (6)