stan/Ecoop2024_TIforWildFJ
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Fix and comment

Browse Source
This commit is contained in:
Andreas Stadelmeier 2024-03-13 18:51:01 +01:00
parent ad34a5dd00
commit 03a7420348
1 changed files with 5 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
introduction.tex
View File

@ -14,7 +14,7 @@ Our algorithm is also capable of finding solutions involving wildcards as shown
%This paper extends a type inference algorithm for Featherweight Java \cite{TIforFGJ} by adding wildcards.
%The last step to create a type inference algorithm compatible to the Java type system.
The algorithm presented in this paper is a slightly improved version of the one in \cite{TIforFGJ} including wildcard support.
The algorithm presented in this paper is a improved version of the one in \cite{TIforFGJ} including wildcard support.
%a modified version of the \unify{} algorithm presented in \cite{plue09_1}.
The input to the type inference algorithm is a Featherweight Java program (example in figure \ref{fig:nested-list-example-typeless}) conforming to the syntax shown in figure \ref{fig:syntax}.
The \fjtype{} algorithm calculates constraints based on this intermediate representation,
@ -520,6 +520,10 @@ $
The \unify{} algorithm only sees the constraints with no information about the program they originated from.
The main challenge was to find an algorithm which computes $\sigma(\wtv{a}) = \rwildcard{X}$ for example \ref{intro-example1} but not for example \ref{intro-example2}.
\subsection{ANF transformation}
The input is transformed to A-normal form.
%TODO: describe ANF syntax (which is different then the one from the wiki: https://en.wikipedia.org/wiki/A-normal_form)
\subsection{Capture Conversion}
The input to our type inference algorithm does not contain let statements.
Those are added after computing a type solution.