# Refocusing (semantics)

In computer science, refocusing is a program transformation used to implement a reduction semantics—i.e., a small-step operational semantics with an explicit representation of the reduction context—more efficiently. It is a step towards implementing a deterministic semantics as a deterministic abstract machine.
A small-step operational semantics defines the meaning of a given program $p_{0}$ as a sequence of one-step reductions that starts with $p_{0}$ and continues with a sequence of reducts $p_{i}$, where $i>0$:
$p_{0}\rightarrow p_{1}\rightarrow p_{2}\rightarrow \cdots$
A one-step reduction from $p_{n}$ to $p_{n+1}$ is achieved by
* locating the smallest potentially reducible term (potential redex) using a given reduction strategy, if this potential redex exists in $p_{n}$ (otherwise $p_{n}$ is irreducible); and
* contracting this potential redex using given contraction rules if it is an actual one (otherwise $p_{n}$ is stuck).
A reduction semantics is a small-step operational semantics with an explicit representation of the context of each potential redex.
Writing $C$ for such context, the sequence of one-step reductions above reads:
$p_{0}=C_{0}[{\mathit {pr}}_{0}]\rightarrow C_{0}[c_{0}]=C_{1}[{\mathit {pr}}_{1}]\rightarrow C_{1}[c_{1}]=C_{2}[{\mathit {pr}}_{2}]\rightarrow C_{2}[c_{2}]\rightarrow \cdots$
where
* $p_{0}$ is first decomposed into the context $C_{0}$ and a potential redex ${\mathit {pr}}_{0}$,
* ${\mathit {pr}}_{0}$ is contracted into the contractum $c_{0}$,
* $C_{0}$ is then recomposed around $c_{0}$ and then decomposed into the context $C_{1}$ and a potential redex ${\mathit {pr}}_{1}$,
* etc.
This succession of decompositions, contractions, and recomposition is depicted as follows:
Refocusing is a deforestation of the successive reducts:
After the initial decomposition, the succession of contractions and refocusings has the structure of a deterministic abstract machine.

## Background

The semantics of a programming language defines the meaning of the programs written in this programming language. Plotkin's Structural Operational Semantics is a small-step semantics where the meaning of a program is defined step by step and where each step is an elementary operation that is carried out with contraction rules.

## Example

Consider the following deterministic language of arithmetic expressions over integers with additions and quotients, in the manner of Hutton's razor.
In OCaml:
So $1+10$ is parsed as Opr (Lit 1, Add, Lit 10) and $11/2$ is parsed as Opr (Lit 11, Quo, Lit 2).
The smallest potentially reducible expressions (potential redexes) are operations over values, and they are carried out with a contraction function that maps an actual redex to an expression and otherwise yields an error message:
The addition of two integers is an actual redex, and so is the quotient of an integer and a nonzero integer. So for example, the expression Opr (Opr (Lit 1, Add, Lit 10), Add, Lit 100), i.e., $(1+10)+100$, reduces to Opr (Lit 11, Add, Lit 100), i.e., $11+100$, the expression Opr (Lit 11, Quo, Lit 2), i.e., $11/2$, reduces to Lit 5, i.e., $5$ since $11=5\cdot 2+1$, and the expression Opr (Opr (Lit 1, Quo, Lit 0), Add, Lit 100), i.e., $(1/0)+100$, reduces to Error "1 / 0".
Say that the reduction strategy is leftmost-innermost (i.e., depth first and left to right), as captured by the following congruence rules:
The following one-step reduction function implements this strategy:
In words:
* a literal reduces to a value;
* if the expression e1 is stuck, then so is the expression Opr (e1, opr, e2), for any expression e2;
* if the expression e1 reduces to an expression e1', then for any expression e2, Opr (e1, opr, e2) reduces to Opr (e1', opr, e2);
* if the expression e1 reduces to a value v1, then
** if the expression e2 is stuck, then so is the expression Opr (e1, opr, e2);
** if the expression e2 reduces to an expression e2', then Opr (e1, opr, e2) reduces to Opr (e1, opr, e2');
** if the expression e2 reduces to a value v2, then Opr (e1, opr, e2) is a potential redex:
*** if this potential redex is an actual one, then contracting it yields an expression; Opr (e1, opr, e2) reduces to this expression;
*** if this potential redex is not an actual one, then Opr (e1, opr, e2) is stuck.
Evaluation is achieved by iterated reduction. It yields either a value or an error message:
This one-step reduction function is structurally recursive. It implements a Structural Operational Semantics for this minimalistic language of arithmetic expressions with errors.
For example, the reduction function implicitly constructs the following proof tree to carry out the reduction step $(1-(5+5))-(2-20)\rightarrow (1-10)-(2-20)$:
Reformatting this proof tree to emphasize the implicit decomposition yields:
A reduction semantics is a small-step operational semantics where the implicit context of a potential redex is made explicit. So one reduction step gives rise to
* constructing the context of the redex,
* contracting this redex, and
* recomposing the context around the contractum to yield the reduct:
And pictorially, an arithmetic expression is evaluated in successive steps:
Transforming the one-step reduction function in Continuation-Passing Style, delimiting the continuation from type value_or_expression_or_stuck -> 'a to type value_or_expression_or_stuck -> value_or_expression_or_stuck, and splitting this delimited continuation into two (one to continue the decomposition and one to recompose, using the type isomorphism between $A+B\rightarrow C$ and $(A\rightarrow C)\times (B\rightarrow C)$) makes it simple to implement the corresponding normalization function:
In the underlined code, the contractum is recomposed and the result is decomposed. This normalization function is said to be reduction-based because it enumerates all the reducts in the reduction sequence.

## Refocusing

Extensionally, the refocusing thesis is that there is no need to reconstruct the next reduct in order to decompose it in the next reduction step. In other words, these intermediate reducts can be deforested.
Pictorially:
Intensionally, the refocusing thesis is that this deforestation is achieved by continuing the decomposition over the contractum in the current context.
In the underlined code, the decomposition is continued. This normalization function is said to be reduction-free because it enumerates none of the reducts in the reduction sequence.
In practice, the two continuations are defunctionalized into traditional first-order, inside-out contexts, which yields an implementation of Felleisen and Hieb's reduction semantics,
a small-step semantics that was designed independently of continuations and defunctionalization, but whose representation—as illustrated here—can be obtained by CPS-transforming and defunctionalizing the representation of a Structural Operational Semantics.
The construction sketched above is completely formalized using the Coq Proof Assistant.

## Applications

Over the years, refocusing has been used for inter-deriving calculi and abstract machines.
Besides the CEK Machine, the Krivine machine, and the SECD machine, examples also include the chemical abstract machine and abstract machines for JavaScript.
Bach Poulsen and Mosses have also used refocusing for implementing Structural Operational Semantics and Modular Structural Operational Semantics.
More broadly, refocusing has been used for deriving type systems and implementations for coroutines,
for going from type checking via reduction to type checking via evaluation,
for deriving a classical call-by-need sequent calculus,
for deriving interpretations of the gradually-typed lambda calculus,
and for full reduction.

## Correctness

Danvy and Nielsen stated conditions for refocusing and proved them informally.
Sieczkowski, Biernacka, and Biernacki formalized refocusing using the Coq Proof Assistant.
Bach Poulsen proved the correctness of refocusing for XSOS using rule induction.
Biernacka, Charatonik, and Zielińska generalized refocusing using the Coq Proof Assistant.
Using Agda, Swiestra proved the refocusing step as part of his formalization of the syntactic correspondence between the $\lambda {\widehat {\rho }}$ calculus with a normal-order reduction strategy and the Krivine machine.
Also using Agda, Rozowski proved the refocusing step as part of his formalization of the syntactic correspondence between the $\lambda {\widehat {\rho }}$ calculus with an applicative-order reduction strategy and the CEK Machine.