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authorChloe Brown <chloe.brown.00@outlook.com>2025-06-24 18:07:37 +0100
committerChloe Brown <chloe.brown.00@outlook.com>2025-06-24 18:07:37 +0100
commit07269d4ab102aac0e3d4995812627d59a316d79b (patch)
treefa4dcfb41338a380c26c125aec3c83249a1b8325
parent57e743e3e48508bafb145c8922f0416b21a55989 (diff)
Fix 92--124.
-rw-r--r--sec/systemt.ltx10
1 files changed, 5 insertions, 5 deletions
diff --git a/sec/systemt.ltx b/sec/systemt.ltx
index a1141ab..cfcd660 100644
--- a/sec/systemt.ltx
+++ b/sec/systemt.ltx
@@ -81,12 +81,12 @@ terms are strongly normalising.
\subsection{Strategies for Encoding Inductive Types}%
\label{subsec:encoding-strategies}
-Inductive types are a useful programming abstraction that is missing from
-System~T. If we are to effectively encode an inductive type, there are three
-operations we would like to use:
+Inductive data types as found in ML are a useful programming
+abstraction that is missing from System~T. If we are to effectively
+encode a data type, there are three operations we need to account for:
\begin{enumerate}
- \item constructors to form values of an inductive type;
- \item folding to fully consume an inductive value;
+ \item constructors to form values of the data type;
+ \item folding to fully consume a value;
\item pattern matching to support iterating on multiple values simultaneously
\end{enumerate}
As a concrete example, consider the pseudocode in \cref{lst:tree-eq}