DataAbstraction chapter: specialized implementations

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Adam Chlipala 2017-02-20 16:56:11 -05:00
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@ -634,6 +634,52 @@ $$\infer{\mt{dequeue}(q) = \cdot}{\mt{rep}(q) = []}
Notice that this specification style can also be viewed as \emph{giving a reference implementation\index{reference implementations of data types} of the data type}, where $\mt{rep}$ shows how to convert back to the reference implementation at any point.
\section{Fixing Parameter Types for Abstract Data Types}
Here's another classic abstract data type: finite sets\index{finite sets}, where we write $\mathbb B$ for the set of Booleans.
\begin{eqnarray*}
\mt{t}(\alpha) &:& \mt{Set} \\
\mt{empty} &:& \mt{t}(\alpha) \\
\mt{add} &:& \mt{t}(\alpha) \times \alpha \to \mt{t}(\alpha) \\
\mt{member} &:& \mt{t}(\alpha) \times \alpha \to \mathbb B
\end{eqnarray*}
A few laws characterize expected behavior, with $\top$ and $\bot$ the respective elements ``true'' and ``false'' of $\mathbb B$.
$$\infer{\mt{member}(\mt{empty}, k) = \bot}{}
\quad \infer{\mt{member}(\mt{add}(s, k), k) = \top}{}
\quad \infer{\mt{member}(\mt{add}(s, k_1), k_2) = \mt{member}(s, k_2)}{k_1 \neq k_2}$$
There is a simple generic implementation of this data type with unsorted lists.
\begin{eqnarray*}
\mt{t} &=& \mt{list} \\
\mt{empty} &=& [] \\
\mt{add}(s, k) &=& \concat{[k]}{s} \\
\mt{member}([], k) &=& \bot \\
\mt{member}(\concat{[k']}{s}, k) &=& k = k' \lor \mt{member}(s, k)
\end{eqnarray*}
However, we can build specialized finite sets for particular element types and usage patterns.
For instance, assume we are working with sets of natural numbers, where we know that most sets contain consecutive numbers.
In those cases, it suffices to store just the lowest and highest elements of sets, and all the set operations run in constant time.
Assume a fallback implementation of finite sets, with type $t_0$ and operations $\mt{empty}_0$, $\mt{add}_0$, and $\mt{member}_0$.
We implement our optimized set type like so, assuming an operation $\mt{fromRange} : \mathbb N \times \mathbb N \to \mt{t}_0$ to turn a range into an ad-hoc set.
\begin{eqnarray*}
\mt{t} &=& \mt{Empty} \mid \mt{Range}(\mathbb N \times \mathbb N) \mid \mt{AdHoc}(\mt{t}_0) \\
\mt{empty} &=& \mt{Empty} \\
\mt{add}(\mt{Empty}, k) &=& \mt{Range}(k, k) \\
\mt{add}(\mt{Range}(n_1, n_2), k) &=& s\textrm{, when $n_1 \leq k \leq n_2$} \\
\mt{add}(\mt{Range}(n_1, n_2), n_1-1) &=& \mt{Range}(n_1-1, n_2)\textrm{, when $n_1 \leq n_2$} \\
\mt{add}(\mt{Range}(n_1, n_2), n_2+1) &=& \mt{Range}(n_1, n_2+1)\textrm{, when $n_1 \leq n_2$} \\
\mt{add}(\mt{Range}(n_1, n_2), k) &=& \mt{AdHoc}(\mt{add}_0(\mt{fromRange}(n_1, n_2), k))\textrm{, otherwise} \\
\mt{add}(\mt{AdHoc}(s), k) &=& \mt{AdHoc}(\mt{add}_0(s, k)) \\
\mt{member}(\mt{Empty}, k) &=& \bot \\
\mt{member}(\mt{Range}(n_1, n_2), k) &=& n_1 \leq k \leq n_2 \\
\mt{member}(\mt{AdHoc}(s), k) &=& \mt{member}_0(s, k)
\end{eqnarray*}
This implementation can be proven to satisfy the finite-set spec, assuming that the baseline ad-hoc implementation does, too.
For workloads that only build sets of consecutive numbers, this implementation can be much faster than the generic list-based implementation, converting quadratic-time algorithms into linear-time.
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