Changeset f845e80 for doc/theses/aaron_moss_PhD/phd/conclusion.tex

Timestamp:

Apr 25, 2019, 2:23:48 PM (5 years ago)

Author:

Aaron Moss <a3moss@…>

Branches:

ADT, aaron-thesis, arm-eh, ast-experimental, cleanup-dtors, enum, forall-pointer-decay, jacob/cs343-translation, jenkins-sandbox, master, new-ast, new-ast-unique-expr, pthread-emulation, qualifiedEnum

Children:

98b4b12

Parents:

69c37cc

Message:

thesis: apply round 2 revisions and strip change bars

File:

• doc/theses/aaron_moss_PhD/phd/conclusion.tex (modified) (1 diff)

doc/theses/aaron_moss_PhD/phd/conclusion.tex

@@ -13 +13 @@
 An alternate approach would be to fork an existing C compiler such as Clang~\cite{Clang}, which would need to be modified to use one of the resolution algorithms discussed here, as well as various other features introduced by Bilson~\cite{Bilson03}.
 
-\cbstart
 More generally, the algorithmic techniques described in this thesis may be useful to implementors of other programming languages. 
 In particular, the demonstration of practical performance for polymorphic return-type inference suggests the possibility of eliding return-type-only template parameters in \CC{} function calls, though integrating such an extension into \CC{} expression resolution in a backwards-compatible manner may be challenging. 
-The \CFA{} expression resolution problem also bears some similarity to the \emph{local type inference} model put forward by Pierce \& Turner \cite{Pierce00} and Odersky \etal{} \cite{Odersky01}; compiler implementors for languages such as Scala \cite{Scala} that perform type inference based on this model may be able to profitably adapt the algorithms and data structures presented in this thesis.
-\cbend
+The \CFA{} expression resolution problem also bears some similarity to the \emph{local type inference} model put forward by Pierce \& Turner \cite{Pierce00} and Odersky \etal{} \cite{Odersky01}; compiler implementors for languages like Scala \cite{Scala}, which performs type inference based on this model, may be able to profitably adapt the algorithms and data structures presented in this thesis.