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In programming language theory, subtyping (also subtype polymorphism or inclusion polymorphism) is a form of type polymorphism in which a subtype is a datatype that is related to another datatype (the supertype) by some notion of substitutability, meaning that program elements, typically subroutines or functions, written to operate on elements of the supertype can also operate on elements of the subtype. If S is a subtype of T, the subtyping relation is often written S <: T, to mean that any term of type S can be safely used in a context where a term of type T is expected. The precise semantics of subtyping crucially depends on the particulars of what "safely used in a context where" means in a given programming language. The type system of a programming language essentially defines its own subtyping relation, which may well be trivial, should the language support no (or very little) conversion mechanisms.


Due to the subtyping relation, a term may belong to more than one type. Subtyping is therefore a form of type polymorphism. In object-oriented programming the term 'polymorphism' is commonly used to refer solely to this subtype polymorphism, while the techniques of parametric polymorphism would be considered generic programming .

Functional programming languages often allow the subtyping of records. Consequently, simply typed lambda calculus extended with record types is perhaps the simplest theoretical setting in which a useful notion of subtyping may be defined and studied. [1] Because the resulting calculus allows terms to have more than one type, it is no longer a "simple" type theory. Since functional programming languages, by definition, support function literals, which can also be stored in records, records types with subtyping provide some of the features of object-oriented programming. Typically, functional programming languages also provide some, usually restricted, form of parametric polymorphism. In a theoretical setting, it is desirable to study the interaction of the two features; a common theoretical setting is system F<:. Various calculi that attempt to capture the theoretical properties of object-oriented programming may be derived from system F<:.

The concept of subtyping is related to the linguistic notions of hyponymy and holonymy. It is also related to the concept of bounded quantification in mathematical logic (see Order-sorted logic). Subtyping should not be confused with the notion of (class or object) inheritance from object-oriented languages; [2] subtyping is a relation between types (interfaces in object-oriented parlance) whereas inheritance is a relation between implementations stemming from a language feature that allows new objects to be created from existing ones. In a number of object-oriented languages, subtyping is called interface inheritance, with inheritance referred to as implementation inheritance.


The notion of subtyping in programming languages dates back to the 1960s; it was introduced in Simula derivatives. The first formal treatments of subtyping were given by John C. Reynolds in 1980 who used category theory to formalize implicit conversions, and Luca Cardelli (1985). [3]

The concept of subtyping has gained visibility (and synonymy with polymorphism in some circles) with the mainstream adoption of object-oriented programming. In this context, the principle of safe substitution is often called the Liskov substitution principle, after Barbara Liskov who popularized it in a keynote address at a conference on object-oriented programming in 1987. Because it must consider mutable objects, the ideal notion of subtyping defined by Liskov and Jeannette Wing, called behavioral subtyping is considerably stronger than what can be implemented in a type checker. (See § Function types below for details.)


Example of subtypes: where bird is the supertype and all others are subtypes as denoted by the arrow in UML notation Inheritance.svg
Example of subtypes: where bird is the supertype and all others are subtypes as denoted by the arrow in UML notation

A simple practical example of subtypes is shown in the diagram, right. The type "bird" has three subtypes "duck", "cuckoo" and "ostrich". Conceptually, each of these is a variety of the basic type "bird" that inherits many "bird" characteristics but has some specific differences. The UML notation is used in this diagram, with open-headed arrows showing the direction and type of the relationship between the supertype and its subtypes.

As a more practical example, a language might allow integer values to be used wherever floating point values are expected (Integer <: Float), or it might define a generic type Number as a common supertype of integers and the reals. In this second case, we only have Integer <: Number and Float <: Number, but Integer and Float are not subtypes of each other.

Programmers may take advantage of subtyping to write code in a more abstract manner than would be possible without it. Consider the following example:


If integer and real are both subtypes of Number, and an operator of comparison with an arbitrary Number is defined for both types, then values of either type can be passed to this function. However, the very possibility of implementing such an operator highly constrains the Number type (for example, one can't compare an integer with a complex number), and actually only comparing integers with integers, and reals with reals, makes sense. Rewriting this function so that it would only accept 'x' and 'y' of the same type requires bounded polymorphism.


In type theory the concept of subsumption [4] is used to define or evaluate whether a type S is a subtype of type T.

A type is a set of values. The set can be described extensionally by listing all the values, or it can be described intensionally by stating the membership of the set by a predicate over a domain of possible values. In common programming languages enumeration types are defined extensionally by listing values. User-defined types like records (structs, interfaces) or classes are defined intensionally by an explicit type declaration or by using an existing value, which encodes type information, as a prototype to be copied or extended.

In discussing the concept of subsumption, the set of values of a type is indicated by writing its name in mathematical italics: T. The type, viewed as a predicate over a domain, is indicated by writing its name in bold: T. The conventional symbol <: means "is a subtype of", and :> means "is a supertype of".

A rule of thumb follow: a subtype is likely to be "bigger/wider/deeper" (its values hold more information) and "fewer/smaller" (the set of values is smaller) than one of its supertypes (which has more restricted information, and whose set of values are a superset of those of the subtype).

In the context of subsumption, the type definitions can be expressed using Set-builder notation, which uses a predicate to define a set. Predicates can be defined over a domain (set of possible values) D. Predicates are partial functions that compare values to selection criteria. For example: "is an integer value greater than or equal to 100 and less than 200?". If a value matches the criteria then the function returns the value. If not, the value is not selected, and nothing is returned. (List comprehensions are a form of this pattern used in many programming languages.)

If there are two predicates, which applies selection criteria for the type T, and which applies additional criteria for the type S, then sets for the two types can be defined:

The predicate is applied alongside as part of the compound predicate S defining S. The two predicates are conjoined, so both must be true for a value to be selected. The predicate subsumes the predicate T, so S <: T.

For example: there is a subfamily of cat species called Felinae, which is part of the family Felidae. The genus Felis, to which the domestic cat species Felis catus belongs, is part of that subfamily.

The conjunction of predicates has been expressed here through application of the second predicate over the domain of values conforming to the first predicate. Viewed as types, Felis <: Felinae <: Felidae.

If T subsumes S (T :> S) then a procedure, function or expression given a value as an operand (input argument or term) will therefore be able to operate over that value as one of type T, because . In the example above, we could expect the function ofSubfamily to be applicable to values of all three types Felidae, Felinae and Felis.

Subtyping schemes

Type theorists make a distinction between nominal subtyping , in which only types declared in a certain way may be subtypes of each other, and structural subtyping , in which the structure of two types determines whether or not one is a subtype of the other. The class-based object-oriented subtyping described above is nominal; a structural subtyping rule for an object-oriented language might say that if objects of type A can handle all of the messages that objects of type B can handle (that is, if they define all the same methods), then A is a subtype of B regardless of whether either inherits from the other. This so-called duck typing is common in dynamically typed object-oriented languages. Sound structural subtyping rules for types other than object types are also well known.[ citation needed ]

Implementations of programming languages with subtyping fall into two general classes: inclusive implementations, in which the representation of any value of type A also represents the same value at type B if A <: B, and coercive implementations, in which a value of type A can be automatically converted into one of type B. The subtyping induced by subclassing in an object-oriented language is usually inclusive; subtyping relations that relate integers and floating-point numbers, which are represented differently, are usually coercive.

In almost all type systems that define a subtyping relation, it is reflexive (meaning A <: A for any type A) and transitive (meaning that if A <: B and B <: C then A <: C). This makes it a preorder on types.

Record types

Width and depth subtyping

Types of records give rise to the concepts of width and depth subtyping. These express two different ways of obtaining a new type of record that allows the same operations as the original record type.

Recall that a record is a collection of (named) fields. Since a subtype is a type which allows all operations allowed on the original type, a record subtype should support the same operations on the fields as the original type supported.

One kind of way to achieve such support, called width subtyping, adds more fields to the record. More formally, every (named) field appearing in the width supertype will appear in the width subtype. Thus, any operation feasible on the supertype will be supported by the subtype.

The second method, called depth subtyping, replaces the various fields with their subtypes. That is, the fields of the subtype are subtypes of the fields of the supertype. Since any operation supported for a field in the supertype is supported for its subtype, any operation feasible on the record supertype is supported by the record subtype. Depth subtyping only makes sense for immutable records: for example, you can assign 1.5 to the 'x' field of a real point (a record with two real fields), but you can't do the same to the 'x' field of an integer point (which, however, is a deep subtype of the real point type) because 1.5 is not an integer (see Variance).

Subtyping of records can be defined in System F<:, which combines parametric polymorphism with subtyping of record types and is a theoretical basis for many functional programming languages that support both features.

Some systems also support subtyping of labeled disjoint union types (such as algebraic data types). The rule for width subtyping is reversed: every tag appearing in the width subtype must appear in the width supertype.

Function types

If T1T2 is a function type, then a subtype of it is any function type S1S2 with the property that T1 <: S1 and S2 <: T2. This can be summarised using the following typing rule:

The argument type of S1S2 is said to be contravariant because the subtyping relation is reversed for it, whereas the return type is covariant. Informally, this reversal occurs because the refined type is "more liberal" in the types it accepts and "more conservative" in the type it returns. This is what exactly works in Scala: a n-ary function is internally a class that inherits the trait (which can be seen as a general interface in Java-like languages), where are the parameter types, and B is its return type; "-" before the type means the type is contravariant while "+" means covariant.

In languages that allow side effects, like most object-oriented languages, subtyping is generally not sufficient to guarantee that a function can be safely used in the context of another. Liskov's work in this area focused on behavioral subtyping, which besides the type system safety discussed in this article also requires that subtypes preserve all invariants guaranteed by the supertypes in some contract. [5] This definition of subtyping is generally undecidable, so it cannot be verified by a type checker.

The subtyping of mutable references is similar to the treatment of function arguments and return values. Write-only references (or sinks) are contravariant, like function arguments; read-only references (or sources) are covariant, like return values. Mutable references which act as both sources and sinks are invariant.

Relationship with inheritance

Subtyping and inheritance are independent (orthogonal) relationships. They may coincide, but none is a special case of the other. In other words, between two types S and T, all combinations of subtyping and inheritance are possible:

  1. S is neither a subtype nor a derived type of T
  2. S is a subtype but is not a derived type of T
  3. S is not a subtype but is a derived type of T
  4. S is both a subtype and a derived type of T

The first case is illustrated by independent types, such as Boolean and Float.

The second case can be illustrated by the relationship between Int32 and Int64. In most object oriented programming languages, Int64 are unrelated by inheritance to Int32. However Int32 can be considered a subtype of Int64 since any 32 bit integer value can be promoted into a 64 bit integer value.

The third case is a consequence of function subtyping input contravariance. Assume a super class of type T having a method m returning an object of the same type (i.e. the type of m is TT, also note that the first argument of m is this/self) and a derived class type S from T. By inheritance, the type of m in S is SS. In order for S to be a subtype of T the type of m in S must be a subtype of the type of m in T, in other words: SS ≤: TT. By bottom-up application of the function subtyping rule, this means: S ≤: T and T ≤: S, which is only possible if S and T are the same. Since inheritance is an irreflexive relation, S can't be a subtype of T.

Subtyping and inheritance are compatible when all inherited fields and methods of the derived type have types which are subtypes of the corresponding fields and methods from the inherited type . [2]


In coercive subtyping systems, subtypes are defined by implicit type conversion functions from subtype to supertype. For each subtyping relationship (S <: T), a coercion function coerce: ST is provided, and any object s of type S is regarded as the object coerceST(s) of type T. A coercion function may be defined by composition: if S <: T and T <: U then s may be regarded as an object of type u under the compound coercion (coerceTUcoerceST). The type coercion from a type to itself coerceTT is the identity function idT

Coercion functions for records and disjoint union subtypes may be defined componentwise; in the case of width-extended records, type coercion simply discards any components which are not defined in the supertype. The type coercion for function types may be given by f'(s) = coerceS2T2(f(coerceT1S1(t))), reflecting the contravariance of function arguments and covariance of return values.

The coercion function is uniquely determined given the subtype and supertype. Thus, when multiple subtyping relationships are defined, one must be careful to guarantee that all type coercions are coherent. For instance, if an integer such as 2 : int can be coerced to a floating point number (say, 2.0 : float), then it is not admissible to coerce 2.1 : float to 2 : int, because the compound coercion coercefloatfloat given by coerceintfloatcoercefloatint would then be distinct from the identity coercion idfloat.

See also


  1. Cardelli, Luca. A semantics of multiple inheritance. In G. Kahn, D. MacQueen, and G. Plotkin, editors, Semantics of Data Types, volume 173 of Lecture Notes in Computer Science, pages 51–67. Springer-Verlag, 1984. Full version in Information and Computation, 76(2/3):138–164, 1988.
  2. 1 2 Cook, Hill & Canning 1990.
  3. Pierce, ch. 15 notes
  4. Benjamin C. Pierce, Types and Programming Languages, MIT Press, 2002, 15.1 "Subsumption", p. 181-182
  5. Barbara Liskov, Jeannette Wing, A behavioral notion of subtyping , ACM Transactions on Programming Languages and Systems, Volume 16, Issue 6 (November 1994), pp. 1811–1841. An updated version appeared as CMU technical report: Liskov, Barbara; Wing, Jeannette (July 1999). "Behavioral Subtyping Using Invariants and Constraints" (PS). Retrieved 2006-10-05.

Related Research Articles

Data type

In computer science and computer programming, a data type or simply type is an attribute of data which tells the compiler or interpreter how the programmer intends to use the data. Most programming languages support basic data types of integer numbers, floating-point numbers, characters and Booleans. A data type constrains the values that an expression, such as a variable or a function, might take. This data type defines the operations that can be done on the data, the meaning of the data, and the way values of that type can be stored. A data type provides a set of values from which an expression may take its values.

In programming languages, a type system is a logical system comprising a set of rules that assigns a property called a type to the various constructs of a computer program, such as variables, expressions, functions or modules. These types formalize and enforce the otherwise implicit categories the programmer uses for algebraic data types, data structures, or other components. The main purpose of a type system is to reduce possibilities for bugs in computer programs by defining interfaces between different parts of a computer program, and then checking that the parts have been connected in a consistent way. This checking can happen statically, dynamically, or as a combination of both. Type systems have other purposes as well, such as expressing business rules, enabling certain compiler optimizations, allowing for multiple dispatch, providing a form of documentation, etc.

In programming languages and type theory, polymorphism is the provision of a single interface to entities of different types or the use of a single symbol to represent multiple different types.

In computer science, a type signature or type annotation defines the inputs and outputs for a function, subroutine or method. A type signature includes the number, types and order of the arguments contained by a function. A type signature is typically used during overload resolution for choosing the correct definition of a function to be called among many overloaded forms.

In knowledge representation, object-oriented programming and design, is-a is a subsumption relationship between abstractions, wherein one class A is a subclass of another class B . In other words, type A is a subtype of type B when A's specification implies B's specification. That is, any object that satisfies A's specification also satisfies B's specification, because B's specification is weaker.

Substitutability is a principle in object-oriented programming stating that, in a computer program, if S is a subtype of T, then objects of type T may be replaced with objects of type S without altering any of the desirable properties of the program. More formally, the Liskov substitution principle (LSP) is a particular definition of a subtyping relation, called (strong) behavioral subtyping, that was initially introduced by Barbara Liskov in a 1988 conference keynote address titled Data abstraction and hierarchy. It is a semantic rather than merely syntactic relation, because it intends to guarantee semantic interoperability of types in a hierarchy, object types in particular. Barbara Liskov and Jeannette Wing described the principle succinctly in a 1994 paper as follows:

Subtype Requirement: Let be a property provable about objects of type T. Then should be true for objects of type S where S is a subtype of T.

In computer science, a tagged union, also called a variant, variant record, choice type, discriminated union, disjoint union, sum type or coproduct, is a data structure used to hold a value that could take on several different, but fixed, types. Only one of the types can be in use at any one time, and a tag field explicitly indicates which one is in use. It can be thought of as a type that has several "cases", each of which should be handled correctly when that type is manipulated. This is critical in defining recursive datatypes, in which some component of a value may have the same type as the value itself, for example in defining a type for representing trees, where it is necessary to distinguish multi-node subtrees and leaves. Like ordinary unions, tagged unions can save storage by overlapping storage areas for each type, since only one is in use at a time.

In computer science, a record is a basic data structure. Records in a database or spreadsheet are usually called "rows".

In computer science, type conversion, type casting, type coercion, and type juggling are different ways of changing an expression from one data type to another. An example would be the conversion of an integer value into a floating point value or its textual representation as a string, and vice versa. Type conversions can take advantage of certain features of type hierarchies or data representations. Two important aspects of a type conversion are whether it happens implicitly (automatically) or explicitly, and whether the underlying data representation is converted from one representation into another, or a given representation is merely reinterpreted as the representation of another data type. In general, both primitive and compound data types can be converted.

In computer science, type safety is the extent to which a programming language discourages or prevents type errors. A type error is erroneous or undesirable program behaviour caused by a discrepancy between differing data types for the program's constants, variables, and methods (functions), e.g., treating an integer (int) as a floating-point number (float). Type safety is sometimes alternatively considered to be a property of a computer program rather than the language in which that program is written; that is, some languages have type-safe facilities that can be circumvented by programmers who adopt practices that exhibit poor type safety. The formal type-theoretic definition of type safety is considerably stronger than what is understood by most programmers.

Class-based programming, or more commonly class-orientation, is a style of object-oriented programming (OOP) in which inheritance occurs via defining classes of objects, instead of inheritance occurring via the objects alone.

Many programming language type systems support subtyping. For instance, if the type Cat is a subtype of Animal, then an expression of type Cat should be substitutable wherever an expression of type Animal is used.

In object-oriented programming, inheritance is the mechanism of basing an object or class upon another object or class, retaining similar implementation. Also defined as deriving new classes from existing ones such as super class or base class and then forming them into a hierarchy of classes. In most class-based object-oriented languages, an object created through inheritance, a "child object", acquires all the properties and behaviors of the "parent object", with the exception of: constructors, destructor, overloaded operators and friend functions of the base class. Inheritance allows programmers to create classes that are built upon existing classes, to specify a new implementation while maintaining the same behaviors, to reuse code and to independently extend original software via public classes and interfaces. The relationships of objects or classes through inheritance give rise to a directed graph.

In mathematical logic and computer science, some type theories and type systems include a top type that is commonly denoted with top or the symbol ⊤. The top type is sometimes called also universal type, or universal supertype as all other types in the type system of interest are subtypes of it, and in most cases, it contains every possible object of the type system. It is in contrast with the bottom type, or the universal subtype, which every other type is supertype of and it is often that the type contains no members at all.

A structural type system is a major class of type system in which type compatibility and equivalence are determined by the type's actual structure or definition and not by other characteristics such as its name or place of declaration. Structural systems are used to determine if types are equivalent and whether a type is a subtype of another. It contrasts with nominative systems, where comparisons are based on the names of the types or explicit declarations, and duck typing, in which only the part of the structure accessed at runtime is checked for compatibility.

EXPRESS (data modeling language)

EXPRESS is a standard data modeling language for product data. EXPRESS is formalized in the ISO Standard for the Exchange of Product model STEP, and standardized as ISO 10303-11.

The circle–ellipse problem in software development illustrates several pitfalls which can arise when using subtype polymorphism in object modelling. The issues are most commonly encountered when using object-oriented programming (OOP). By definition, this problem is a violation of the Liskov substitution principle, one of the SOLID principles.

In type theory, bounded quantification refers to universal or existential quantifiers which are restricted ("bounded") to range only over the subtypes of a particular type. Bounded quantification is an interaction of parametric polymorphism with subtyping. Bounded quantification has traditionally been studied in the functional setting of System F<:, but is available in modern object-oriented languages supporting parametric polymorphism (generics) such as Java, C# and Scala.

In object-oriented programming, behavioral subtyping is the principle that subclasses should satisfy the expectations of clients accessing subclass objects through references of superclass type, not just as regards syntactic safety but also as regards behavioral correctness. Specifically, properties that clients can prove using the specification of an object's presumed type should hold even though the object is actually a member of a subtype of that type.

Object-oriented programming (OOP) is a programming paradigm based on the concept of "objects", which can contain data and code: data in the form of fields, and code, in the form of procedures.




Cook, William R.; Hill, Walter; Canning, Peter S. (1990). Inheritance is not subtyping. Proc. 17th ACM SIGPLAN-SIGACT Symp. on Principles of Programming Languages (POPL). pp. 125–135. CiteSeerX . doi:10.1145/96709.96721. ISBN   0-89791-343-4.
  • Reynolds, John C. Using category theory to design implicit conversions and generic operators. In N. D. Jones, editor, Proceedings of the Aarhus Workshop on Semantics-Directed Compiler Generation, number 94 in Lecture Notes in Computer Science. Springer-Verlag, January 1980. Also in Carl A. Gunter and John C. Mitchell, editors, Theoretical Aspects of Object-Oriented Programming: Types, Semantics, and Language Design (MIT Press, 1994).

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