computer science

Multiple dispatch

Multiple dispatch is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Multiple dispatch rather than just read about it. In short: Multiple dispatch or multimethods is a feature of some programming languages in which a function or method can be dynamically dispatched based on the run-time (dynamic) type or, in the more general case, some other attribute of more than one of its arguments. This is a generalization of single-dispatch polymorphism where a function or method call is dynamically dispatched based on the derived type of the object on w…

Key takeaways

Multiple dispatch belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Multiple dispatch to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Multiple dispatch from memory before moving on to harder problems.

Reference excerpt

Multiple dispatch or multimethods is a feature of some programming languages in which a function or method can be dynamically dispatched based on the run-time (dynamic) type or, in the more general case, some other attribute of more than one of its arguments. This is a generalization of single-dispatch polymorphism where a function or method call is dynamically dispatched based on the derived type of the object on which the method has been called. Multiple dispatch routes the dynamic dispatch to the implementing function or method using the combined characteristics of one or more arguments.

Understanding dispatch Developers of computer software typically organize source code into named blocks variously called subroutines, procedures, subprograms, functions, or methods. The code in the function is executed by calling it – executing a piece of code that references its name. This transfers control temporarily to the called function; when the function's execution has completed, control is typically transferred back to the instruction in the caller that follows the reference. Function names are usually selected so as to be descriptive of the function's purpose. It is sometimes desirable to give several functions the same name, often because they perform conceptually similar tasks, but operate on different types of input data. In such cases, the name reference at the function call site is not sufficient for identifying the block of code to be executed. Instead, the number and type of the arguments to the function call are also used to select among several function implementations. In more conventional, i.e., single-dispatch object-oriented programming languages, when invoking a method (sending a message in Smalltalk, calling a member function in C++), one of its arguments is treated specially and used to determine which of the (potentially many) classes of methods of that name is to be applied. In many languages, the special argument is indicated syntactically; for example, a number of programming languages put the special argument before a dot in making a method call: special.method(other, arguments, here), so that lion.sound() would produce a roar, whereas sparrow.sound() would produce a chirp. In contrast, in languages with multiple dispatch, the selected method is simply the one whose arguments match the number and type of the function call. There is no special argument that owns the function/method carried out in a particular call. Multiple dispatch should be distinguished from function overloading, in which static typing information, such as a term's declared or inferred type (or base type in a language with subtyping) is used to determine which of several possibilities will be used at a given call site, and that determination is made at compile or link time (or some other time before program execution starts) and is thereafter invariant for a given deployment or run of the program. Many languages such as C++ offer robust function overloading but do not offer dynamic multiple dispatch (C++ only permits dynamic single dispatch through use of virtual functions).

Data types When working with languages that can discriminate data types at compile time, selecting among the alternatives can occur then. The act of creating such alternative functions for compile time selection is usually referred to as overloading a function. In programming languages that defer data type identification until run time (i.e., late binding), selection among alternative functions must occur then, based on the dynamically determined types of function arguments. Functions whose alternative implementations are selected in this manner are referred to most generally as multimethods. There is some run-time cost associated with dynamically dispatching function calls. In some languages, the distinction between overloading and multimethods can be blurred, with the compiler determining whether compile time selection can be applied to a given function call, or whether slower run time dispatch is needed.

Issues There are several known issues with dynamic-dispatch, both single and multiple. While many of these issues are solved for single-dispatch, which has been a standard feature in object-oriented programming languages for decades, these issues become more complicated in the multiple-dispatch case.

Expressiveness and modularity In most popular programming languages, source code is delivered and deployed in granules of functionality which we will here call packages; actual terminology for this concept varies between language. Each package may contain multiple type, value, and function definitions, packages are often compiled separately in languages with a compilation step, and a non-cyclical dependency relationship may exist. A complete program is a set of packages, with a main package which may depend on several other packages, and the whole program consisting of the transitive closure of the dependency relationship. The so-called expression problem relates to the ability for code in a depending package to extend behaviors (functions or datatypes) defined in a base package from within an including package, without modifying the source to the base package. Traditional single-dispatch OO languages make it trivial to add new datatypes but not new functions; traditional functional languages tend to have the opposite effect, and multiple dispatch, if implemented correctly, allows both. It is desirable for an implementation of multiple dispatch to have the following properties:

… excerpt ends here. Continue reading the full article.

Illustrations

Worked examples

Example 1 — a first encounter with Multiple dispatch

Start with the simplest possible case. Write down what Multiple dispatch claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Multiple dispatch before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Multiple dispatch ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Multiple dispatch

In research: Multiple dispatch appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Multiple dispatch in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Multiple dispatch is common in secondary-school and first-year university syllabi. It links to neighbouring topics Method (computer programming), Polymorphism (computer science), Programming language comparisons, so understanding it makes those chapters shorter.
In everyday life: Look for Multiple dispatch outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Multiple dispatch in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Multiple dispatch means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Multiple dispatch out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Multiple dispatch in simple terms?

Why does Multiple dispatch matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Multiple dispatch?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Multiple dispatch.