Flow-sensitive typing
{{Type systems}}
In programming language theory, flow-sensitive typing (also called flow typing or occurrence typing) is a type system where the type of an expression depends on its position in the control flow.
In statically typed languages, a type of an expression is determined by the types of the sub-expressions that compose it. However, in flow-sensitive typing, an expression's type may be updated to a more specific type if it follows an operation that validates its type. Validating operations can include type predicates, imperative updates, and control flow.
Examples
= Ceylon =
See the following example in Ceylon which illustrates the concept:
// Object? means the variable "name" is of type Object or else null
void hello(Object? name) {
if (is String name) {
// "name" now has type String in this block
print("Hello, ``name``!");
// and it is possible to call String methods on the variable
print(" String.size is ``name.size``");
}
else if (exists name) {
// "name" now has type Object in this block
print("Hello, object ``name``!");
}
else {
print("Hello, world!");
}
}
hello(null);
hello(1);
hello("John Doe");
and which outputs:
Hello, world!Hello, object 1!
Hello, John Doe!
String.size is 8
= Kotlin =
See this example in Kotlin:
fun hello(obj: Any) {
// A type cast fails if `obj` is not a String
obj as String
// Since the type cast did not fail, `obj` must be a String!
val l = obj.length
println("'$obj' is a string of length $l")
}
hello("Mooooo")
Benefits
This technique coupled with type inference reduces the need for writing type annotations for all variables or to do type casting, like is seen with dynamic languages that use duck typing. It reduces verbosity and makes for terser code, easier to read and modify.
It can also help language implementers provide implementations that execute dynamic languages faster by predicting the type of objects statically.{{cite web | url=http://blog.jooq.org/2014/12/11/the-inconvenient-truth-about-dynamic-vs-static-typing | title=The Inconvenient Truth About Dynamic vs. Static Typing | publisher=blog.jooq.org | date=11 December 2014 | access-date=11 March 2016 | author=Lukas Eder}}
Finally, it increases type safety and can prevent problems due to null pointers{{How|date=March 2020|title=The citation later is for the quote, flow sensitive typing doesn't seem to improve null-safety, a null-safe type system will. Possible confusion as these languages have nullable/non-nullable types, as checking null-safety through flow-sensitive typing generally equates to a null check without it}}, labeled by C.A.R. Hoare—the null reference inventor—as "the billion dollar mistake"{{cite web
|url=http://www.infoq.com/presentations/Null-References-The-Billion-Dollar-Mistake-Tony-Hoare
|title=Null References: The Billion Dollar Mistake
|publisher=InfoQ.com
|date=2009-08-25
|author=Tony Hoare
|quote=I call it my billion-dollar mistake. It was the invention of the null reference in 1965. At that time, I was designing the first comprehensive type system for references in an object oriented language (ALGOL W). My goal was to ensure that all use of references should be absolutely safe, with checking performed automatically by the compiler. But I couldn't resist the temptation to put in a null reference, simply because it was so easy to implement. This has led to innumerable errors, vulnerabilities, and system crashes, which have probably caused a billion dollars of pain and damage in the last forty years.}}
From a Programming Languages perspective, it's reasonable to say that flow-sensitive typing is the feature that finally made it possible to build usable type-safe programming languages with union types and without rampant dynamic checking. Until this point, attempts to add this feature to languages such as Scheme generally resulted in intractably large type representations. One example of a system with limited support for union types is Wright and Cartwright's "Soft Scheme."{{cite journal |last1=Wright |first1=Andrew |last2=Cartwright |first2=Robert |title=A practical soft type system for scheme |journal=ACM Transactions on Programming Languages and Systems |date=1 Jan 1997 |volume=19 |issue=1 |pages=87--152 |doi=10.1145/239912.239917 |url=https://dl.acm.org/doi/abs/10.1145/239912.239917 |access-date=2024-05-04}}
Implementations
Typed Scheme, a type system for Scheme, was the first type system with this feature.{{cite web |title=The Design and Implementation of Typed Scheme {{!}} POPL, 2008 |url=https://dl.acm.org/doi/10.1145/1328438.1328486 |website=dl.acm.org}} Its successor, Typed Racket (a dialect of Racket), is also based on occurrence typing.{{cite web |title=5 Occurrence Typing |url=https://docs.racket-lang.org/ts-guide/occurrence-typing.html |website=docs.racket-lang.org}} Shortly after Typed Scheme, David J. Pearce independently reinvented flow-typing in Whiley.{{cite web | url=http://whiley.org/2010/09/22/on-flow-sensitive-types-in-whiley/ | title=On Flow-Sensitive Types in Whiley | publisher=whiley.org | date=22 September 2010 | access-date=11 March 2016 | author=David J. Pearce | archive-date=11 March 2016 | archive-url=https://web.archive.org/web/20160311184700/http://whiley.org/2010/09/22/on-flow-sensitive-types-in-whiley/ | url-status=dead }}{{cite web | url=http://whiley.org/guide/typing/flow-typing/ | title=Whiley - Flow Typing | publisher=whiley.org | date=8 April 2012 | access-date=11 March 2016 | author=David J. Pearce | archive-date=11 March 2016 | archive-url=https://web.archive.org/web/20160311184703/http://whiley.org/guide/typing/flow-typing/ | url-status=dead }}
Typed JavaScript observed that in "scripting" languages, flow-typing depends on more than conditional predicates; it also depends on state and control flow.{{cite web | url=https://cs.brown.edu/~sk/Publications/Papers/Published/gsk-flow-typing-theory/ | title=Typing Local Control and State Using Flow Analysis | access-date=14 November 2016}} This style has since been adopted in languages like Ceylon,{{cite web | url=http://ceylon-lang.org/documentation/1.2/introduction/#typesafe_null_and_flow_sensitive_typing | title=Ceylon - Quick introduction - Typesafe null and flow-sensitive typing | publisher=ceylon-lang.org | access-date=11 March 2016}} TypeScript{{cite web |url=https://blogs.msdn.microsoft.com/typescript/2014/11/18/typescript-1-4-sneak-peek-union-types-type-guards-and-more | title=TypeScript 1.4 sneak peek: union types, type guards, and more | publisher=blogs.msdn.microsoft.com | date=18 November 2014 | access-date=11 March 2016 | author=Ryan Cavanaugh}} and Facebook Flow.{{cite web | url=https://code.facebook.com/posts/1505962329687926/flow-a-new-static-type-checker-for-javascript | title=Flow, a new static type checker for JavaScript | publisher=code.facebook.com | date=18 November 2014 | access-date=11 March 2016 |author=Avik Chaudhuri |author2=Basil Hosmer |author3=Gabriel Levi}}
There are also a few languages that don't have union types but do have nullable types, that have a limited form of this feature that only applies to nullable types, such as C#,{{cite web |title=Design with nullable reference types |url=https://docs.microsoft.com/en-us/dotnet/csharp/tutorials/nullable-reference-types#create-respondents-and-get-answers-to-the-survey |website=docs.microsoft.com |language=en-us}} Kotlin,{{cite web | url=https://kotlinlang.org/docs/reference/null-safety.html | title=Null Safety | publisher=kotlinlang.org | access-date=11 March 2016}}{{cite web | url=https://kotlinlang.org/docs/reference/typecasts.html | title=Type Checks and Casts | publisher=kotlinlang.org | access-date=11 March 2016}} and Lobster.{{cite web |title=The Lobster Type System |url=http://aardappel.github.io/lobster/type_checker.html#the-trouble-with-nil |website=aardappel.github.io}}
Alternatives
Pattern matching reaches the same goals as flow-sensitive typing, namely reducing verbosity and making up for terser code, easier to read and modify.
It achieves this is in a different way, it allows to match the type of a structure, extract data out of it at the same time by declaring new variable. As such, it reduces the ceremony around type casting and value extraction. Pattern matching works best when used in conjunction with algebraic data types because all the cases can be enumerated and statically checked by the compiler.
See this example mock for Java:{{cite web |title=JEP 441: Pattern Matching for switch| url=https://openjdk.org/jeps/441|website=openjdk.org |language=en-us |date=19 September 2023 |access-date=14 November 2023 |author=Gavin Bierman and Brian Goetz}}
int eval(Node n) {
return switch(n) {
// try to type cast "Node" into "IntNode", and create the variable "i" of type "int".
// If that works, then return the value of "i"
case IntNode(int i) -> i;
// try to type cast "Node" into "NegNode", and create the variable "n" of type "Node".
// If that works, then return the negation of evaluating the "n" node
case NegNode(Node n) -> -eval(n);
// try to type cast "Node" into "AddNode", and create the variables "left" and "right" of type "Node".
// If that works, then return the addition of evaluating the "left" and "right" nodes
case AddNode(Node left, Node right) -> eval(left) + eval(right);
// try to type cast "Node" into "MulNode", and create the variables "left" and "right" of type "Node".
// If that works, then return the multiplication of evaluating the "left" and "right" nodes
case MulNode(Node left, Node right) -> eval(left) * eval(right);
// no "default" because the compiler knows all the possible cases have been enumerated
};
}
In a statically typed language, the advantage of pattern matching over flow-sensitive typing is that the type of a variable always stays the same: it does not change depending on control flow. When writing down the pattern to be matched, a new variable is declared that will have the new type.