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If the mutable set were allowed a covariant type parameter, both variables below could refer to the same mutable object:The broad view accepts any value, including a string. The narrow view still promises that deletion returns an Int, yet the sole stored value is that string. This violates type safety:This is covariance failure for a mutable collection. The input occurrence in add(x: T) conflicts with the positive occurrence in the result of delete. Keeping a generic type invariance restriction prevents the unsafe aliasing. The example uses an initially empty set so that the problematic deletion result is forced.

For a specified programming language and execution model, type safety commonly follows from two properties: a closed expression satisfying a typing judgment is either a value or can take an execution step, and taking a step preserves its type. Proofs proceed by structural induction on derivations, using capture-avoiding substitution for function calls. Repeated preservation keeps the remaining expression typed; the first property then rules out getting stuck at an operation outside the model's permitted cases. This argument does not imply termination or correctness of an arbitrary specification. ^[ref]

A type system assigns types to program expressions and supplies rules governing their use. A type constrains permitted operations: in our teaching programming language, int admits integer addition, bool supplies true and false for conditions, and a function type specifies an argument type and a result type. Storage as bits alone does not explain these distinctions; the type system determines whether an expression can serve as an argument, a condition or an operand.

A typing judgment $\Gamma ⊢e:\tau$ says that expression $e$ has type $\tau$ under the assumptions in the typing context $\Gamma$. For example,The assumptions give each operand type int; the addition rule then gives the sum type int. Changing $y$ to type bool prevents this derivation. Our teaching programming language has distinct int and bool types and no implicit conversions between them.

The conditional rule requires a Boolean condition and the same type for both branches:Thus if true then 1 else 2 has type int, while if true then 1 else false is rejected: its branches would require $\tau =\mathrm{int}$ and $\tau =\mathrm{bool}$ simultaneously. Even a branch that will not execute is checked by this rule. This is a rule of this particular type system; a different programming language can choose different rules. ^[ref]

The useful feature is compositional reasoning: after checking the parts, a rule explains how to check the whole. The function type diagram shows this for a call. Type inference can discover the required types automatically, and type variables let one express relationships that recur across many concrete types. The result is both a practical early error detector and a small, readable derivation explaining why an expression fits its intended use.

The guarantee depends on the rules and execution model. Type safety can exclude specified failures such as adding a Boolean or calling an integer as a function. It does not by itself establish every desired runtime property or guarantee that execution terminates. A type system that permits unrestricted recursion can accept a computation that runs forever; exception handling also needs its own account of permitted outcomes.