In computer programming, a thunk is a subroutine that is created, often automatically, to assist a call to another subroutine. Thunks are primarily used to represent an additional calculation that a subroutine needs to execute, or to call a routine that does not support the usual calling mechanism. They have a variety of other applications to compiler code generation and in modular programming.
The term originated as a jocular derivative of "think".
The early years of compiler research saw broad experimentation with different evaluation strategies. A key question was how to compile a subroutine call if the arguments can be arbitrary mathematical expressions rather than constants. One approach, known as "call by value," calculates all of the arguments before the call and then passes the resulting values to the subroutine. In the rival "call by name" approach, the subroutine receives the unevaluated argument expression and must evaluate it.
A simple implementation of "call by name" might substitute the code of an argument expression for each appearance of the corresponding parameter in the subroutine, but this can produce multiple versions of the subroutine and multiple copies of the expression code. As an improvement, the compiler can generate a helper subroutine, called a thunk, that calculates the value of the argument. The address of this helper subroutine is then passed to the original subroutine in place of the original argument, where it can be called as many times as needed. Peter Ingerman first described thunks in reference to the ALGOL 60 programming language, which supported call-by-name evaluation.
Although the software industry largely standardized on call-by-value and call-by-reference evaluation, active study of call-by-name continued in the functional programming community. This research produced a series of lazy evaluation programming languages in which some variant of call-by-name is the standard evaluation strategy. Compilers for these languages, such as the Glasgow Haskell Compiler, have relied heavily on thunks, with the added feature that the thunks save their initial result so that they can avoid recalculating it; this is known as memoization.