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\lecture{3} %% Lecture number
\title{Equivalence, Reductions and Normal Forms}   %% Title of lecture
\lecturer{Benyah Shaparenko}
%\author{Ymir Vigfusson, Daria Sorokina}  %% name of scribe
\date{30 August 2006}    %% Date of lecture
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\begin{document}

\maketitle

%\section{Administrativa}
%\begin{itemize}
%\item No class on Monday (Labor day)
%\item Wednesday: Radu Rugina
%\item Problem Set 1 is due on Wednesday, the paper component is due on 5PM, and
%\texttt{lambda.sml} is due on midnight.
%\end{itemize}

\section{Term Equivalence}

When are two terms equal?  This is not as simple a question as it may seem.  As _intensional_ objects, two terms are equal if they are identical.  As _extensional_ objects, however, two terms should be equal if they represent the same function.  But this is not as simple as it sounds, and in fact defining a precise mathematical model for defining equivalence of two $\lambda$-terms is far from straightforward.

One way of approaching the problem is to try all possible arguments and compare the results.  However, one immediate problem is to know what the valid arguments are.  We also need to say what happens when one or both of the computations can loop infinitely (diverge).

For starters, let us assume that we are working with an evaluation strategy such as CBV or CBN that is _deterministic_, which means that there is at most one next $\beta$-reduction that can be performed.  We say that a term $e$ _terminates_ or _converges_ if there is a finite sequence of reductions
\[
e\ \ \rightarrow\ \ e'\ \ \rightarrow\ \ e''\ \ \rightarrow\ \ \cdots\ \ \rightarrow v
\]
where $v$ is a value.  We write $e\Downarrow v$ when this happens, and we write $e\Downarrow$ when $e\Downarrow v$ for some $v$.  The other possibility is that it keeps on reducing forever without ever arriving at a value.  When this happens, we say that $e$ _diverges_ and write $e \Uparrow$.

With CBN or CBV, there are infinitely many divergent terms.
One example is $\Omega$ which was defined in the last lecture. 
In some sense, all divergent terms are equal to one another, since none of them produce a value.

We are now ready to give a better notion of equality.

\subsection{Equality of Terms}

Intuitively, two terms will be considered equal if in every context, either
\begin{itemize}
\item they both converge and produce the same value, or
\item they both diverge.
\end{itemize}
A _context_ is just a term $C[\,\cdot\,]$ with a single occurrence of a distinguished special variable, called the _hole_, and $C[e]$ denotes the context $C[\,\cdot\,]$ with the hold replaced by the term $e$.  Here we do not do safe substitution, but just stuff $e$ into the hole with abandon, allowing free variables to be captured.  Then we then define equality in the following way:
\[
e_1 = e_2 \ \ \iff\ \ \mbox{for all contexts } C[\,\cdot\,],\ C[e_1] \Downarrow v \mbox{ iff } C[e_2] \Downarrow v.
\]

It turns out that without loss of generality, we can simplify the definition to 
\[
e_1 = e_2 \ \ \iff\ \ \mbox{for all contexts } C[\,\cdot\,],\ C[e_1] \Downarrow \mbox{ iff } C[e_2] \Downarrow,
\]
because if they converge to different values, it is possible to devise a context that causes one to converge and the other to diverge.

This may sound simple in the mathematical sense, but of course
it is undecidable to determine whether two terms are equal.  Given the relationship between
the $\lambda$-calculus and Turing machines, if we could decide equality, 
then we would have solved the halting problem.

A conservative approximation (but unfortunately still undecidable) is the following.  Let $e_1$ and $e_2$ be terms, and suppose that $e_1$ and $e_2$ converge to the same value.  Then $e_1=e_2$.  This is especially useful for compiler optimization.

\section{Rewrite Rules}

\subsection{Recap---$\beta$-reduction}

Recall that _$\beta$-reduction_ is the following rule:
\[
(\lambda x.e_1) e_2\ \ \xrightarrow{\beta}\ \ \subst{e_1}{e_2}x.
\]
An instance of the left-hand side is called a _redex_ and the corresponding instance of the right-hand side is called the _contractum_.  For example, 
\[
\lambda x.\underbrace{(\lambda y.y)x}_{\beta \text{ redex}}\ \ \xrightarrow{\beta}\ \ \lambda x.x
\]
Note that in CBV, $\lambda x.(\lambda y.y)x$ is a value (we cannot apply a $\beta$-reduction inside the body of an abstraction) so we cannot apply this reduction. 

\subsection{$\alpha$-reduction}

In $\lambda x.x z$ the name of the bound variable $x$ doesn't really matter. 
This term is semantically the same as $\lambda y.y z$.
Renamings like that are known as _$\alpha$-reductions_.
In an $\alpha$-reduction, the new bound variable must be chosen so as to avoid capture.
If a term $\alpha$-reduces to another term, then the two terms are said to be \emph{$\alpha$-equivalent}.
This defines an equivalence relation on the set of terms, denoted $e_1 =_\alpha e_2$.

Recall the definition of free variables $\FV e$ of a term $e$.  In general we have
\[
\lambda x.e\ \ =_\alpha\ \ \lambda y.\subst eyx \text { if } y \notin FV(e).
\]
The proviso $y \notin FV(e)$ is to avoid the capture of a free occurrences of $y$ in $e$ as a result of the renaming.

When writing a $\lambda$-interpreter, the job of looking for $\alpha$-renamings doesn't 
seem all that practical.  However, we can use them to improve our earlier definition of equality:
\[
\mbox{If $e_1 \Downarrow v_1$, $e_2 \Downarrow v_2$, and $v_1 =_\alpha v_2$, then $e_1 = e_2$}.
\]

We can create a _Stoy diagram_ for a closed term in the following manner.
Instead of writing $\lambda x.(\lambda y.y)x$, we write $\lambda \cdot.(\lambda \cdot.\cdot)\cdot$ 
and connect variables that are the same by edges.  Then $\alpha$-equivalent terms have the same Stoy-diagram.

\subsection{$\eta$-reduction}

Here is another notion of equality.  Compare the terms $e$ and $\lam x{ex}$.
If these two terms are both applied to an argument $e'$, then they will both reduce to $e\,e'$,
provided $x$ has no free occurrence in $e$.  Formally,
\[
(\lambda x.e_1 x)e_2 \xrightarrow{\beta} e_1 e_2 \text{ if } x \notin FV(e_1).
\]

This says that $e$ and $\lam x{ex}$ behave the same way as functions and should be considered equal.  Another way of stating this is that $e$ and $\lam x{ex}$ behave the same way in all contexts of the form $[\,\cdot\,]\,e'$.

This gives rise to a reduction rule called _$\eta$-reduction_:
\[
\lambda x.ex\ \ \xrightarrow{\eta}\ \ e\ \ \text{ if } x \notin FV(e).
\]
The reverse operation, called _$\eta$-expansion_, is practical as well.

In practice, $\eta$-expansion is used to delay divergence by trapping 
expressions inside $\lambda$ terms.

The $\eta$ rule may not be sound with respect to our earlier notion of equality, depending on our reduction strategy.  For example, $\lam x{ex}$ is a value in CBV, but reductions might be possible in $e$ and it might diverge.

\section{The Church--Rosser Property}

In the classical $\lambda$-calculus, no reduction strategy is specified, and no restrictions are placed on the order of reductions.  Any redex may be chosen to be reduced next.  A $\lambda$-term in general may have many redexes, so the process is nondeterministic.  We can think of a reduction strategy as a mechanism for resolving the nondeterminism, but in the classical $\lambda$-calculus, no such strategy is specified.  A _value_ in this case is just a term containing no redexes.  Such a term is said to be in _normal form_.

This makes it very difficult to define equality.  One sequence of reductions may terminate, but another may not.  It is even conceivable that different terminating reduction sequences result in different values.  Luckily, it turns out that the latter cannot happen.

It turns out that the $\lambda$-calculus is _confluent_ (also known as the _Church--Rosser_ property) under $\alpha$- and $\beta$-reductions.  Confluence says that if $e$ reduces by some sequence of reductions to $e_1$, and if $e$ also reduces by some other sequence of reductions to $e_2$, then there exists an $e_3$ such that both $e_1$ and $e_2$ reduce to $e_3$.
\[
\begin{matrix}
   & & e_1 & & \\
   & \nearrow & & \searrow & \\
e  & &    & & e_3 \\
   & \searrow & & \nearrow & \\
   & & e_2 & & 
\end{matrix}
\]
It follows that up to $\alpha$-equivalence, normal forms are unique.  For if $e\Downarrow v_1$ and $e\Downarrow v_2$, and if $v_1$ and $v_2$ are in normal form, then by confluence they must be $\alpha$-equivalent.  Moreover, regardless of the order of previous reductions, it is always possible to get to the unique normal form if it exists.

However, note that it is still possible for a reduction sequence not to terminate, even if the term has a normal form.  For example, $(\lam x{\lam yy})\Omega$ has a nonterminating CBV reduction sequence
\[
(\lambda xy.y) \Omega\ \ \xrightarrow{\beta}\ \ (\lambda xy.y) \Omega\ \ \xrightarrow{\beta}\ \ \cdots
\]
but a terminating CBV reduction sequence, namely
\[
(\lam x{\lam yy})\Omega\ \ \xrightarrow{\beta}\ \ \lam yy.
\]
It may be difficult to determine the most efficient way to expedite termination.  But even if we get stuck in a loop, the Church--Rosser theorem guarantees that it is always possible to get unstuck, provided the normal form exists.

In call-by-name (CBN), the leftmost redex is always reduced first.  This strategy is also called _normal order_.  It turns out that CBN is guaranteed to find the normal form if it exists, albeit not necessarily in the most efficient way.  Call-by-value (CBV) is also called _applicative order_.


In C, the order of evaluation of arguments is implementation-specific.
Also, C does not specify in what order operands work.  Hence C is not confluent.
For example, the value of the expression $(x=1) + x$ is 2 if the left operand of $+$ is evaluated first,
$x+1$ if the right operand is evaluated first.
The language specification does not say which, so it depends on the implementation.

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