StaDyn (programming language) explained

StaDyn
Paradigm:Object oriented
Designer:Francisco Ortin[1]
Developer:Computational Reflection research group[2] of the University of Oviedo
Latest Release Version:2.2.1
Typing:Hybrid static and dynamic typing, gradual typing, strong, inferred
Implementations:C#
Influenced By:C#, OCaml, StrongTalk, Boo
Programming Language:C#
Platform:Common Language Infrastructure (.NET Framework)
License:MIT License[3]

StaDyn is an object-oriented general-purpose programming language for the .NET platform that supports both static and dynamic typing in the same programming language.

The StaDyn compiler gathers type information for the dynamically typed code. That type information is used to detect type errors at compilation time and to perform significant optimizations. For that purpose, it provides type reconstruction (inference), flow-sensitive types, union and intersection types, constraint-based typing, alias analysis and method specialization.Its first prototype appeared in 2007, as a modification of C# 3.0. Type inference was supported by including var as a new type, unlike C#, which only offers var to define initialized local variables. Flow-sensitive types of var references are inferred by the compiler, providing type-safe duck typing.[4] When a more lenient approach is required by the programmer, the dynamictype could be used instead of var. Although type inference is still performed, dynamic references behave closer to those in dynamic languages.

StaDyn is designed by Francisco Ortin[1] from the University of Oviedo. The language has been implemented by different members of the Computational Reflection research group,[2] including Miguel Garcia, Jose Baltasar García Perez-Schofield and Jose Quiroga, besides Francisco Ortin.

The name StaDyn is a portmanteau of static and dynamic, denoting its aim to provide the benefits of both static and dynamic typing.

Code samples

Variables with different types

Just like dynamic languages, variables may hold different types in the same scope:

using System;class Program

The age variable is first inferred as string, so it is safe to get its Length property. Then, it holds an integer, so age++ is a valid expression. The compiler detects an error in the last line, since Length is no longer provided by age.

The generated code does not use a single Object variable to represent age, but two different variables whose types are string and int. This is achieved with a modification of the algorithm to compute the SSA form.[5] This makes the generated code to be more efficient, since runtime type conversions are not required.

Flow-sensitive types

var and dynamic variables can hold flow-sensitive types:

using System;class Program

It is safe to get the Message property from exception because both ApplicationException and SystemException provide that property. Otherwise, a compiler error is shown. In this way, StaDyn provides a type-safe static duck-typing system.

In the following program:

using System;class Program

The Message property is not provided by String, so a compiler error is shown for exception.Message. However, if we declare exception as dynamic, the previous program is accepted by the compiler. dynamic is more lenient than var, following the flavor of dynamic languages. However, static type checking is still performed. This is shown in the last line of code, where the compiler shows an error for exception.Unknown even if exception is declared as dynamic. This is because neither of the three possible types (ApplicationException, SystemException and String) supports the Unknown message.[6]

Although dynamic and var types can be used explicitly to obtain safer or more lenient type checking, the dynamism of single var references can also be modified with command-line options, XML configuration files and a plugin for Visual Studio.[7]

Type inference of fields

var and dynamic types can be used as object fields:

class Wrapper

class Test

The Wrapper class can wrap any type. Each time we call the set method, the type of attribute is inferred as the type of the argument. Each object has a potentially different type of attribute, so its type is stored for every single instance rather than for the whole class. In this way, the two lines indicated in the code above report compilation errors. A type-based alias analysis algorithm is implemented to support this behavior.[8]

Constraint-based types

Let's analyze the following method:

public static var upper(var parameter)

The type of parameter and the function return value are inferred by the compiler. To that aim, a constraint is added to the type of the upper method: the argument must provide a ToUpper method with no parameters. At each invocation, the constraint will be checked. Additionally, the return type of upper will be inferred as the return type of the corresponding ToUpper method implemented by the argument.[9]

The programmer may use either var or dynamic to declare parameter, changing the way type checking is performed upon method invocation. Let's assume that the argument passed to upper holds a flow-sensitive type (e.g., the ApplicationException, SystemException or String exception variable in the code above). With var, all the possible types of the argument must provide ToUpper; with dynamic, at least one type must provide ToUpper.

Runtime performance

The type information gathered by StaDyn is used to perform significant optimizations in the generated code: [10] the number of type inspections and type casts are reduced, reflection is avoided, frequent types are cached, and methods with constraints are specialized. The point of all the optimizations is to reduce the number of type-checking operations performed at runtime, which is the main performance penalty of most dynamic languages. Many of those type checks are undertaken earlier by the StaDyn compiler. A detailed evaluation of the runtime performance of StaDyn is detailed in.[4]

See also

References

  1. Web site: Francisco Ortin . May 17, 2022 . uniovi.es.
  2. Web site: Computational Reflection Research Group . May 17, 2022 . uniovi.es.
  3. Web site: StaDyn Download . May 17, 2022 . uniovi.es.
  4. 10.1016/j.knosys.2019.05.013 . Rule-based program specialization to optimize gradually typed code . Francisco Ortin . Miguel Garcia . Sean McSweeney . Knowledge-Based Systems . 2019 . 179 . 145–173 . 182002303 . 10651/53505 . free .
  5. 10.1093/comjnl/bxw108. SSA Transformations to Facilitate Type Inference in Dynamically Typed Code. Jose Quiroga . Francisco Ortin . The Computer Journal. 2017.
  6. 10.1016/j.ipl.2010.12.006 . Union and intersection types to support both dynamic and static typing . Francisco Ortin . Miguel Garcia . Information Processing Letters . 2011 . 111 . 6 . 278–286 . 10651/8732 . free .
  7. 10.1016/j.jvlc.2014.04.002 . Static type information to improve the IDE features of hybrid dynamically and statically typed languages . Francisco Ortin . Francisco Morero . Anton Morant . Journal of Visual Languages & Computing . 2014 . 25 . 4 . 346–362 .
  8. 10.1049/iet-sen.2009.0070 . Including both static and dynamic typing in the same programming language . Francisco Ortin . Daniel Zapico . J.B.G. Perez-Schofield . Miguel Garcia . IET Software . 2010 . 4 . 4 . 268 . 10651/9769 . free .
  9. 10.1093/comjnl/bxr067 . Type Inference to Optimize a Hybrid Statically and Dynamically Typed Language . Francisco Ortin . The Computer Journal . 2011 . 54 . 11 . 1901–1924 . 10651/11411 . free .
  10. 10.1002/spe.2291 . Design and implementation of an efficient hybrid dynamic and static typing language . Miguel Garcia . Francisco Ortin . Jose Quiroga . Software: Practice and Experience . 2016 . 46 . 2 . 199–226 . 2065468 .

External links