Add 4 steps of TI introduction
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introduction.tex
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introduction.tex
@ -32,27 +32,22 @@ are infered and inserted by our algorithm.
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To outline the contributions in this paper we will list the advantages and improvements to smiliar type inference algorithms:
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\begin{description}
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\item[Global Type Inference for Featherweight Java] \cite{TIforFGJ} is a predecessor to our algorithm.
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The algorithm presented in this paper is an improved version
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with the biggest change being the added wildcard support.
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The type inference algorithm presented here supports Java Wildcards.
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% Proven sound on type rules of Featherweight Java, which are also proven to produce sound programs
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% implication rules that follow the subtyping rules directly. Easy to understand soundness proof
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% capture conversion is needed
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\textit{Example:} The type inference algorithm for Generic Featherweight Java produces \texttt{Object} as the return type of the
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\texttt{genBox} method in listing \ref{lst:intro-example-typeless}
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whereas our type inference algorithm will infer the type solution shown in listing \ref{lst:intro-example-typed}.
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whereas our type inference algorithm will infer the type solution shown in listing \ref{lst:intro-example-typed}
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involving a wildcard type.
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\item[Type Unification for Java with Wildcards]
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An existing unification algorithm for Java with wildcards \cite{plue09_1} states the same capabilities,
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but exposes some errors when it comes to method invocations.
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Especially the problems shown in chapter \ref{challenges} are handled incorrectly.
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Whereas our type inference algorithm is based on a Featherweight Java calculus \cite{WildFJ} and it's proven sound subtyping rules.
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The algorithm presented in this paper is able to solve all those challenges correctly
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and it's correctness is proven using a Featherweight Java calculus \cite{WildFJ}.
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%But they are all correctly solved by our new type inference algorithm presented in this paper.
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The central piece of this type inference algorithm, the \unify{} process, is described with implication rules (chapter \ref{sec:unify}).
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We try to keep the branching at a minimal amount to improve runtime behavior.
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Also the transformation steps of the \unify{} algorithm are directly related to the subtyping rules of our calculus.
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There are no informal parts in our \unify{} algorithm.
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It solely consist out of transformation rules which are bound to simple checks.
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\item[Java Type Inference]
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Standard Java provides type inference in a restricted form % namely {Local Type Inference}.
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which only works for local environments where the surrounding context has known types.
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@ -285,39 +280,89 @@ lo.add(new Integer(1)); // error!
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\end{minipage}
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\end{figure}
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\section{Global Type Inference Algorithm}
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% \begin{description}
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% \item[input] \tifj{} program
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% \item[output] type solution
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% \item[postcondition] the type solution applied to the input must yield a valid \letfj{} program
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% \end{description}
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%Our algorithm is an extension of the \emph{Global Type Inference for Featherweight Generic Java}\cite{TIforFGJ} algorithm.
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Listings \ref{lst:addExample}, \ref{lst:addExampleLet}, \ref{lst:addExampleCons}, and
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\ref{lst:addExampleSolution} showcase our global type inference algorithm step by step.
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In this example we know that the type of the variable \texttt{l} is an existential type and has to undergo a capture conversion
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before being passed to a method call.
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This is done by converting the program to A-Normal form \ref{lst:addExampleLet},
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which introduces a let statement defining a new variable \texttt{v}.
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Afterwards constraints are generated \ref{lst:addExampleCons}.
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During the constraint generation step the type of the variable \texttt{v} is unknown
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and given the type placeholder $\tv{v}$.
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Due to the call to the method \texttt{add} it is clear that \texttt{v} has to be a subtype of
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any kind of \texttt{List} resulting in the constraint $\tv{v} \lessdotCC \exptype{List}{\wtv{a}}$.
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Here we introduce a capture constraint ($\lessdotCC$) %a new type of subtype constraint
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expressing that the left side of the constraint is subject to a capture conversion.
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%Additionally we use a wildcard placeholder $\wtv{a}$ as a type parameter for \texttt{List}.
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A correct Featherweight Java program including all type annotations and an explicit capture conversion via let statement is shown in listing \ref{lst:addExampleSolution}.
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This program can be deducted from the type solution of our \unify{} algorithm presented in chapter \ref{sec:unify}.
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In the body of the let statement the type $\wctype{\wildcard{X}{\type{Object}}{\type{String}}}{List}{\rwildcard{X}}$
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becomes $\exptype{List}{\rwildcard{X}}$ and the wildcard $\wildcard{X}{\type{Object}}{\type{String}}$ is free and can be used as
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a type parameter to method call \texttt{<X>add(v, "String")}.
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% The input to our type inference algorithm is a modified version of the calculus in \cite{WildcardsNeedWitnessProtection} (see chapter \ref{sec:tifj}).
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% First \fjtype{} (see section \ref{chapter:constraintGeneration}) generates constraints
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% and afterwards \unify{} (section \ref{sec:unify}) computes a solution for the given constraint set.
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% Constraints consist out of subtype constraints $(\type{T} \lessdot \type{T})$ and capture constraints $(\type{T} \lessdotCC \type{T})$.
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% \textit{Note:} a type $\type{T}$ can either be a named type, a type placeholder or a wildcard type placeholder.
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% A subtype constraint is satisfied if the left side is a subtype of the right side according to the rules in figure \ref{fig:subtyping}.
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% \textit{Example:} $\exptype{List}{\ntv{a}} \lessdot \exptype{List}{\type{String}}$ is fulfilled by replacing type placeholder $\ntv{a}$ with the type $\type{String}$.
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% Subtype constraints and type placeholders act the same as the ones used in \emph{Type Inference for Featherweight Generic Java} \cite{TIforFGJ}.
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% The novel capture constraints and wildcard placeholders are needed for method invocations involving wildcards.
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% The central piece of this type inference algorithm, the \unify{} process, is described with implication rules (chapter \ref{sec:unify}).
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% We try to keep the branching at a minimal amount to improve runtime behavior.
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% Also the transformation steps of the \unify{} algorithm are directly related to the subtyping rules of our calculus.
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% There are no informal parts in our \unify{} algorithm.
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% It solely consist out of transformation rules which are bound to simple checks.
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%show input and a correct letFJ representation
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%TODO: first show local type inference and explain lessdotCC constraints. then show example with global TI
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\begin{figure}[h]
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\begin{minipage}{0.49\textwidth}
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\begin{lstlisting}[style=tfgj, caption=Valid Java program, label=lst:addExample]
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<A> List<A> add(List<A> l, A v) ...
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<A> List<A> add(List<A> l, A v)
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List<? super String> l = ...;
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add(l, "String");
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\end{lstlisting}
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\end{minipage}\hfill
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\begin{minipage}{0.49\textwidth}
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\begin{lstlisting}[style=letfj, caption=\TamedFJ{} representation, label=lst:addExampleLet]
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\begin{lstlisting}[style=tamedfj, caption=\TamedFJ{} representation, label=lst:addExampleLet]
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<A> List<A> add(List<A> l, A v)
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List<? super String> l = ...;
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let v:(*@$\tv{v}$@*) = l
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in add(v, "String");
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\end{lstlisting}
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\end{minipage}\\
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\begin{minipage}{0.49\textwidth}
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\begin{lstlisting}[style=constraints, caption=Constraints, label=lst:addExampleCons]
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(*@$\tv{v} \lessdot \wctype{\wildcard{X}{\type{String}}{\bot}}{List}{\rwildcard{X}}$@*)
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(*@$\tv{v} \lessdotCC \exptype{List}{\wtv{a}}$@*)
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(*@$\type{String} \lessdot \wtv{a}$@*)
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\end{lstlisting}
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\end{minipage}\hfill
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\begin{minipage}{0.49\textwidth}
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\begin{lstlisting}[style=letfj, caption=Type solution, label=lst:addExampleSolution]
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<A> List<A> add(List<A> l, A v)
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List<? super String> l = ...;
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let l2:(*@$\wctype{\wildcard{X}{\type{Object}}{\type{String}}}{List}{\rwildcard{X}}$@*) = l
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in <X>add(l2, "String");
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\end{lstlisting}
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\end{minipage}
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\end{figure}
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In listing \ref{lst:addExample} Java uses local type inference \cite{JavaLocalTI}
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to determine the type parameters to the \texttt{add} method call.
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A \TamedFJ{} representation including all type annotations and an explicit capture conversion via let statement is shown in listing \ref{lst:addExampleLet}.
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%In \letfj{} there is no local type inference and all type parameters for a method call are mandatory (see listing \ref{lst:addExampleLet}).
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%If wildcards are involved the so called capture conversion has to be done manually via let statements.
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%A let statement \emph{opens} an existential type.
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In the body of the let statement the \textit{capture type} $\wctype{\wildcard{X}{\type{Object}}{\type{String}}}{List}{\rwildcard{X}}$
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becomes $\exptype{List}{\rwildcard{X}}$ and the wildcard $\wildcard{X}{\type{Object}}{\type{String}}$ is free and can be used as
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a type parameter to \texttt{<X>add(...)}.
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%This is a valid Java program where the type parameters for the polymorphic method \texttt{add}
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%are determined by local type inference.
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One problem is the divergence between denotable and expressable types in Java \cite{semanticWildcardModel}.
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A wildcard in the Java syntax has no name and is bound to its enclosing type:
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$\exptype{List}{\exptype{List}{\type{?}}}$ equates to $\exptype{List}{\wctype{\rwildcard{X}}{List}{\rwildcard{X}}}$.
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@ -349,26 +394,6 @@ and \texttt{shuffle} can be invoked with the type parameter $\rwildcard{X}$:
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let l2d' : (*@$\wctype{\rwildcard{X}}{List}{\exptype{List}{\rwildcard{X}}}$@*) = l2d in <X>shuffle(l2d')
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\end{lstlisting}
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\section{Global Type Inference Algorithm}
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% \begin{description}
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% \item[input] \tifj{} program
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% \item[output] type solution
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% \item[postcondition] the type solution applied to the input must yield a valid \letfj{} program
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% \end{description}
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%Our algorithm is an extension of the \emph{Global Type Inference for Featherweight Generic Java}\cite{TIforFGJ} algorithm.
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The input to our type inference algorithm is a modified version of the calculus in \cite{WildcardsNeedWitnessProtection} (see chapter \ref{sec:tifj}).
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First \fjtype{} (see section \ref{chapter:constraintGeneration}) generates constraints
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and afterwards \unify{} (section \ref{sec:unify}) computes a solution for the given constraint set.
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Constraints consist out of subtype constraints $(\type{T} \lessdot \type{T})$ and capture constraints $(\type{T} \lessdotCC \type{T})$.
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\textit{Note:} a type $\type{T}$ can either be a named type, a type placeholder or a wildcard type placeholder.
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A subtype constraint is satisfied if the left side is a subtype of the right side according to the rules in figure \ref{fig:subtyping}.
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\textit{Example:} $\exptype{List}{\ntv{a}} \lessdot \exptype{List}{\type{String}}$ is fulfilled by replacing type placeholder $\ntv{a}$ with the type $\type{String}$.
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Subtype constraints and type placeholders act the same as the ones used in \emph{Type Inference for Featherweight Generic Java} \cite{TIforFGJ}.
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The novel capture constraints and wildcard placeholders are needed for method invocations involving wildcards.
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\begin{recap}\textbf{TI for FGJ without Wildcards:}
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\TFGJ{} generates subtype constraints $(\type{T} \lessdot \type{T})$ consisting of named types and type placeholders.
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For example the method invocation \texttt{concat(l, new Object())} generates the constraints
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