cargaji/tfm-report
cargaji
/
tfm-report
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

deleted old tex files

This commit is contained in:
Carlos Galindo 2019-12-06 19:36:15 +00:00
parent aaa086e90b
commit 54f6b9848f
6 changed files with 0 additions and 964 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

134
incremental_slicing.tex
View File

@ -1,134 +0,0 @@
% !TEX encoding = UTF-8
% !TEX spellcheck = en_GB
% !TEX root = paper.tex
\chapter{Main explanation?}
\section{First definition of the SDG}
\label{sec:first-def-sdg}
The system dependence graph (SDG) is a method for program slicing that was first proposed by Horwitz, Reps and Blinkey \cite{HorwitzRB88}. It builds upon the existing control flow graph (CFG), defining dependencies between vertices of the CFG, and building a program dependence graph (PDG), which represents them. The system dependence graph (SDG) is then build from the assembly of the different PDGs (each representing a method of the program), linking each method call to its corresponding definition. Because each graph is built from the previous one, new constructs can be added with to the CFG, without the need to alter the algorithm that converts CFG to PDG and then to SDG. The only modification possible is the redefinition of a dependency or the addition of new kinds of dependence.
The language covered by the initial proposal was a simple one, featuring procedures with modifiable parameters and basic instructions, including calls to procedures, variable assignments, arithmetic and logic operators and conditional instructions (branches and loops): the basic features of an imperative programming language. The control flow graph was as simple as the programs themselves, with each graph representing one procedure. The instructions of the program are represented as vertices of the graph and are split into two categories: statements, which have no effect on the control flow (assignments, procedure calls) and predicates, whose execution may lead to one of multiple ---though traditionally two--- paths (conditional instructions). Statements are connected sequentially to the next instruction. Predicates have two outgoing edges, each connected to the first statement that should be executed, according to the result of evaluating the conditional expression in the guard of the predicate.
\begin{definition}[Control Flow Graph~\cite{???}]
A \emph{control flow graph} $G$ of a program $P$ is a tuple $\langle N, E \rangle$.
\end{definition}
To build the PDG and then the SDG, some dependencies must be extracted from the CFG, which are defined as follows:
\begin{definition}[Postdominance]
Vertex $b$ \textit{postdominates} vertex $b$ if and only if $a \neq b$ and $b$ is on every path from $a$ to the ``End'' vertex.
\end{definition}
\begin{definition}[Control dependency]
\label{def:ctrl-dep}
Vertex $b$ is \textit{control dependent} on vertex $a$ ($a \ctrldep b$) if and only if $b$ postdominates one but not all of $a$'s successors. It follows that a vertex with only one successor cannot be the source of control dependence.
\end{definition}
\begin{definition}[Data dependency]
Vertex $b$ is \textit{data dependent} on vertex $a$ ($a \datadep b$) if and only if $a$ may define a variable $x$, $b$ may use $x$ and there an $x$-definition free path from $a$ to $b$.\footnote{The initial definition of data dependency was further split into in-loop data dependencies and the rest, but the difference is not relevant for computing the slices in the SDG.}
\end{definition}
It should be noted that variable definitions and uses can be computed for each statement independently, analyzing the procedures called by it if necessary. In general, any instruction uses all variables that appear in it, save for the left-hand side of assignments. Similarly, no instruction defines variables, except those in the left-hand side of assignments. The variables used and defined by a procedure call are those used and defined by its body.
With the data and control dependencies, the PDG may be built, by replacing the edges from the CFG by data and control dependence edges. The first tends to be represented as a thin solid line, and the latter as a thick solid line. In the examples, data dependencies will be thin solid red lines.
The organization of the vertices of the PDG tends to resemble a tree graph, with the ``Start'' node in the position of the root (at the top), and the ``End'' node typically omitted. The control dependence edges structure the tree vertically. In the case that a vertex is control dependent on multiple vertices, it will be placed one level below the lowest source of control dependency. With a programming language this simple, cyclical control dependencies do not appear, but should they do so in further sections, the instructions are sorted top to bottom in the order they appear in the program. Horizontally, the vertices are sorted by their order in the program, left to right, in order to make the graph more readable. Data dependency edges are placed without reordering the nodes of the graph. In the examples given, edges like $a \datadep a$ or $b \ctrldep b$ may be omitted, as they are not relevant for later use of the graph. Please be noted that the location of the vertices is irrelevant for the slicing algorithm, and the aforementioned sorting rules are just for consistency with previous papers on the topic and to ease the visualization of programs.
Finally, the SDG is built from the combination of all the PDGs that compose the program. Each call vertex is connected to the ``Start'' of the corresponding procedure. All edges that connect PDGs are represented with dashed lines.
\begin{figure}
\begin{minipage}{0.3\linewidth}
\begin{lstlisting}
proc main() {
a = 10;
b = 20;
f(a, b);
print(a);
}
proc f(x, y) {
while (x > y) {
x = x - 1;
}
print(x);
}
\end{lstlisting}
\end{minipage}
\begin{minipage}{0.6\linewidth}
\includegraphics[width=0.3\linewidth]{img/cfgsimple}
\includegraphics[width=0.65\linewidth]{img/cfgsimple2}
\end{minipage}
\includegraphics[width=0.5\linewidth]{img/pdgsimple}
\includegraphics[width=0.49\linewidth]{img/pdgsimple2}
\includegraphics[width=0.6\linewidth]{img/sdgsimple}
\includegraphics[width=0.4\linewidth]{img/legendsimple}
\caption{A simple program with its CFGs (top right), PDGs (center) and SDG (bottom).}
\label{fig:sdg-loop}
\end{figure}
\subsubsection{Procedures and data dependencies}
The only thing left to explain before introducing more constructs into the language is the passing of parameters. Most programming language accept a variable number of input parameters and one output parameter. In the case of input parameters passed by reference, or constructs such as structs or classes, modifying a field of a parameter may modify the original variable. In order to deal with everything related to parameter passing, including global variables, class fields, etc. there is a small extension to be made to the CFG and PDG.
In the CFG, the ``Start'' and ``End'' nodes contain a list of assignments, inputting and outputting respectively the appropriate values, as can be seen in the example. Consequently, every vertex that contains a procedure or function call pack and unpack the arguments. For every variable $x$ that is used in a procedure, every call to it must be preceded by $x_{in} = x$, and the procedures's ``Start'' vertex must contain $x = x_{in}$. The opposite happens when a variable must be ``outputted''\carlos{replace}: before the ``End'' node, the value must be packed ($x_{out} = x$), and after each call, the value must be assigned to the corresponding variable ($x = x_{out}$). Parameters may be assigned as $par^i_{in} = expr_i$ (where $i$ is the index of the parameter in the procedure definition, $par^i$ is the name of the parameter and $expr_i$ is the expression in the $i^{th}$ position in the procedure call) in the call vertex, and parameters whose modifications inside the procedure are passed back to the calling procedure must be extracted as $var = par^i_{out}$ (where $var$ is the name of the variable ---passed by reference--- in the calling procedure).\carlos{What if object/struct passed by value?} As an addition, in the SDG, an extra edge is added (summary edge), which represents the dependencies that the input variables have on the outputs. This allows the algorithm to know the dependencies without traversing the corresponding function.
All these additions are added as extra lines in the ``Start'', ``End'' and calling vertices.
When building the PDG, all additions (variable assignments) are split into their own vertices, and are control dependent on them.
Data dependencies no longer flow throw the call vertex, but throw the appropriate child, which minimizes the size of the slice produced.
As an example, figure~\ref{fig:sdg-loop} shows the three stages of a program, from CFG to SDG.
The construction of the CFG is straight-forward, save for the packing and unpacking of variables in the start, end and call vertices.
In the PDG, the statements are split, control and data dependencies replace the control flow edges.
Finally, both PDGs are linked via call and parameter (input and output) edges, forming the SDG.
Summary edges are placed according to the data and control flow of the method call, and the graph is complete.
\section{Unconditional control flow}
Even though the initial definition of the SDG was useful to compute slices, the language covered was not enough for the typical language of the 1980's, which included (in one form or another) unconditional control flow.
Therefore, one of the first additions contributed to the algorithm to build system dependence graphs was the inclusion of unconditional jumps, such as ``break'', ``continue'', ``goto'' and ``return'' statements (or any other equivalent).
A naive representation would be to treat them the same as any other statement, but with the outgoing edge landing in the corresponding instruction (outside the loop, at the loop condition, at the method's end, etc.).
An alternative approach is to represent the instruction as an edge, not a vertex, connecting the previous statement with the next to be executed.
Both of these approaches fail to generate a control dependence from the unconditional jump, as the definition of control dependence (see Definition~\ref{def:ctrl-dep}) requires a vertex to have more than one successor for it to be possible to be a source of control dependence.
From here, there stem two approaches: the first would be to redefine control dependency, in order to reflect the real effect of these instructions ---as some authors~\cite{DanBHHKL11} have tried to do--- and the second would be to alter the creation of the SDG to ``create'' those dependencies, which is the most widely--used solution.
The most popular approach was proposed by Ball and Horwitz\cite{BalH93}, and represents unconditional jumps as a \textsl{pseudo--predicate}.
The true edge would lead to the next instruction to be executed, and the false edge would be non-executable or \textit{dummy} edges, connected to the instruction that would be executed were the unconditional jump a \textit{nop}.
The consequence of this solution is that every instruction placed after the unconditional jump is control dependent on the jump, as can be seen in Figure~\ref{fig:break-graphs}.
In the example, when slicing with respect to variable $a$ on line 5, every statement would be included, save for ``print(a)''.
Line 4 is not strictly necessary in this example ---in the context of weak slicing---, but is included nonetheless.
In the original paper, the transformation is proved to be complete, but not correct, as for some examples, the slice includes more unconditional jumps that would be strictly necessary, even for weak slicing.
Ball and Horwitz theorize that a more correct approach would be possible, if it weren't for the limitation of slices to be a subset of statements of the program, in the same order as in the original.
\begin{figure}
\centering
\begin{minipage}{0.3\linewidth}
\begin{lstlisting}
static void f() {
int a = 1;
while (a > 0) {
if (a > 10) break;
a++;
}
System.out.println(a);
}
\end{lstlisting}
\end{minipage}
\begin{minipage}{0.6\linewidth}
\includegraphics[width=0.4\linewidth]{img/breakcfg}
\includegraphics[width=0.59\linewidth]{img/breakpdg}
\end{minipage}
\caption{A program with unconditional control flow, its CFG (center) and PDG(right).}
\label{fig:break-graphs}
\end{figure}
\section{Exceptions}
As seen in section~\ref{sec:intro-exception}, exception handling in Java adds two constructs: the \texttt{throw} and the \texttt{try-catch} statements. The first one resembles an unconditional control flow statement, with an unknown (on compile time) destination. The exception will be caught by a \texttt{catch} of the corresponding type or a supertype ---if it exists. Otherwise, it will crash the corresponding thread (or in single-threaded programs, stop the Java Virtual Machine).
\subsection{\texttt{throw} statement}
The \texttt{throw} statement is represented as a ``return'', but instead of leaving the method through the ``End'' node, a new ``Error end'' or ``Error exit'' is created. This represents the
\subsection{\texttt{try-catch} statement}
% vim: set noexpandtab:ts=2:sw=2:wrap

423
introduction.tex
View File

@ -1,423 +0,0 @@
% !TEX encoding = UTF-8
% !TEX spellcheck = en_GB
% !TEX root = paper.tex
\chapter{Introduction}
\section{Program slicing}
\textsl{Program slicing} \cite{Wei81,Sil12} is a debugging technique that
answers the question: ``which parts of a program affect a given statement and
variable?'' The statement and the variable are the basic input to create a slice
and are called the \textsl{slicing criterion}. The criterion can be more
complex, as different slicing techniques may require additional pieces of input.
The \textsl{slice} of a program is the list of statements from the original
program ---which constitutes a valid program---, whose execution will result in
the same values for the variable (selected in the slicing criterion) being read
by a debugger in the selected statement.
There exist two fundamental dimensions along which the problem of slicing can be
proposed:
\begin{itemize}
\item \textsl{Static} or \textsl{dynamic}: slicing can be performed
statically or dynamically.
\textsl{Static slicing} \cite{Wei81} is a slice which considers all
possible executions of the program, only taking into account the
semantics of the programming language.
In contrast, \textsl{dynamic slicing} \cite{KorL88} limits the slice to
the statements present in an execution log. The slicing criterion is
expanded to include a position in the log that corresponds to one
instance of the selected statement, making it much more specific. It may
help finding a bug related to indeterministic behavior (such as a random
or pseudo-random number generator), but must be recomputed for each case
being analyzed.
\item \textsl{Backward} or \textsl{forward}: \textsl{backward slicing}
\cite{Wei81} is generally more used, because it looks at the statements
that affect the slicing criterion. In contrast, \textsl{forward slicing}
\cite{BerC85} computes the statements that are affected by the slicing
criterion. There also exists a mixed approach called \textsl{chopping}
\cite{JacR94}, which is used to find all statements that affect or are
affected by the slicing criterion.
\end{itemize}
Since the definition of program slicing, the most extended form of slicing has
been \textsl{static backward slicing}, which obtains the list of statements that
affect the value of a variable in a given statement, in all possible executions
of the program (i.e., for any input data).
\begin{definition}[Strong static backward slice \cite{Wei81,HorwitzRB88}]
\label{def:strong-slice}
\carlos{Falta ver exactamente cuál es la cita correcta.}
Given a program $P$ and a slicing criterion $C = \langle s,v \rangle$, where
$s$ is a statement and $v$ is a set of variables in $P$ (the variables may
or may not be used in $s$), $S$ is the \textsl{strong slice} of $P$ with
respect to $C$ if $S$ has the following properties:
\begin{enumerate}
\item $S$ is an executable program.
\item $S \subseteq P$, or $S$ is the result of removing code from $P$.
\item For any input $I$, the values produced on each execution of $s$
for each of the variables in $v$ is the same when executing $S$ as
when executing $P$. \label{enum:exact-output}
\end{enumerate}
\end{definition}
\begin{definition}[Weak static backward slice \cite{RepY89}]
\label{def:weak-slice}
\carlos{Comprobar cita y escribir formalmente}
Same as definition~\ref{def:strong-slice}, but
property~\ref{enum:exact-output} is altered to: For any input $I$, the
values produced on each execution of $s$ for each of the variables in $v$
when running $S$ is a prefix of the values produced when running $P$.
\end{definition}
Both definitions (\ref{def:strong-slice} and~\ref{def:weak-slice}) are
used throughout the literature, with some cases favoring the first and some the
second. Though the definitions come from the corresponding citations, the naming
was first used in a control dependency analysis by Danicic~\cite{DanBHHKL11},
where slices which produce the same output as the original are named
\textsl{strong}, and those where the original is a prefix of the slice,
\textsl{weak} \carlos{Se podría argumentar que con el slice débil es suficiente
para debugging, ya que si un error se presenta en el original, aparecerá también
en el programa fragmentado}.
See table~\ref{tab:slice-weak} for an example; with each row showing the values
logged at the slicing criterion from the execution of 4 different programs.
The first is the original, which computes $3!$. Slice A is one slice, whose
execution is identical and therefore is a strong slice. Slice B is correct but
continues producing values after the original stops ---a weak slice. It would
fit the relaxed definition but not a strong one. Slice C is incorrect, as the
values differ from the original. Some data or control dependency has not been
included in the slice and the program are behaving in a different way.
\begin{table}
\centering
\label{tab:slice-weak}
\begin{tabular}{r | r | r | r | r | r }
Iteration & \textbf{1} & \textbf{2} & \textbf{3} & \textbf{4} & \textbf{5} \\ \hline
Original & 1 & 2 & 6 & - & - \\ \hline
Slice A & 1 & 2 & 6 & - & - \\ \hline
Slice B & 1 & 2 & 6 & 24 & 120 \\ \hline
Slice C & 1 & 1 & 3 & 5 & 8 \\
\end{tabular}
\caption{Execution logs of different slices and their original program.}
\end{table}
Program slicing is a language--agnostic tool, but the original proposal by
Weiser~\cite{Wei81} covers a simple imperative programming language.
Since, the literature has been expanded by dozens of authors, that have
described and implemented slicing for more complex structures, such as
uncontrolled control flow~\cite{HorwitzRB88}, global variables~\cite{???},
exception handling~\cite{AllH03}; and for other programming paradigms, such as
object-oriented languages~\cite{???} or functional languages~\cite{???}.
\carlos{Se pueden poner más, faltan las citas correspondientes.}
\subsection{The System Dependence Graph (SDG)}
There exist multiple approaches to compute a slice from a given program and
criterion, but the most efficient and broadly use data structure is the System
Dependence Graph (SDG), first introduced by Horwitz, Reps and
Blinkey~\cite{HorwitzRB88}. It is computed from the program's statements, and
once built, a slicing criterion is chosen, the graph traversed using a specific
algorithm, and the slice obtained. Its efficiency resides in the fact that for
multiple slices that share the same program, the graph must only be built once.
On top of that, building the graph has a complexity of $\mathcal{O}(n^2)$ with
respect to the number of statements in a program, but the traversal is linear
with respect to the number of nodes in the graph (each corresponding to a
statement).
The SDG is a directed graph, and as such it has vertices or nodes, each
representing an instruction in the program ---barring some auxiliary nodes
introduced by some approaches--- and directed edges, which represent the
dependencies among nodes. Those edges represent various kinds of dependencies
---control, data, calls, parameter passing, summary--- which will be defined in
section~\ref{sec:first-def-sdg}.
To create the SDG, first a \textsl{control flow graph} is built for each method
in the program, then its control and data dependencies are computed, resulting
in the \textsl{program dependence graph}. Finally, all the graphs from every
method are joined into the SDG. This process will be explained at greater
lengths in section~\ref{sec:first-def-sdg}.
%TODO: marked for removal --- this process is repeated later in ref{sec:first-deg-sdg}
%\begin{description}
%\item[CFG] The control flow graph is the representation of the control
%dependencies in a method of a program. Every statement has an edge from
%itself to every statement that can immediately follow. This means that
%most will only have one outgoing edge, and conditional jumps and loops
%will have two. The graph starts in a ``Begin'' or ``Start'' node, and
%ends in an ``End'' node, to which the last statement and all return
%statements are connected. It is created directly from the source code,
%without any need for data dependency analysis.
%\item[PDG] The program dependence graph is the result of restructuring and
%adding data dependencies to a CFG. All statements are placed below and
%connected to a ``Begin'' node, except those which are inside a loop or
%conditional block. Then data dependencies are added (red or dashed
%edges), adding an edge between two nodes if there is a data dependency.
%\item[SDG] Finally, the system dependence graph is the interconnection of
%each method's PDG. When a call is made, the input arguments are passed
%to subnodes of the call, and the result is obtained in another subnode.
%There is an edge from the call to the beginning of the corresponding
%method, and an extra type of edge exists: \textsl{summary edges}, which
%summarize the data dependencies between input and output variables.
%\end{description}
An example is provided in figure~\ref{fig:basic-graphs}, where a simple
multiplication program is converted to CFG, then PDG and finally SDG. For
simplicity, only the CFG and PDG of \texttt{multiply} are shown. Control
dependencies are black, data dependencies red and summary edges blue.
\begin{figure}
\centering
\begin{minipage}{0.4\linewidth}
\begin{lstlisting}
int multiply(int x, int y) {
int result = 0;
while (x > 0) {
result += y;
x--;
}
System.out.println(result);
return result;
}
\end{lstlisting}
\end{minipage}
\begin{minipage}{0.59\linewidth}
\includegraphics[width=\linewidth]{img/multiplycfg}
\end{minipage}
\includegraphics[width=\linewidth]{img/multiplypdg}
\includegraphics[width=\linewidth]{img/multiplysdg}
\caption{A simple multiplication program, its CFG, PDG and SDG}
\label{fig:basic-graphs}
\end{figure}
\subsection{Metrics}
There are four relevant metrics considered when evaluating a slicing algorithm:
\begin{description}
\item[Completeness] The solution includes all the statements that affect the
slice. This is the most important feature, and almost all publications
achieve at least completeness. Trivial completeness is easily
achievable, as simple as including the whole program in the slice.
\item[Correctness] The solution excludes all statements that don't affect
the slice. Most solutions are complete, but the degree of correctness is
what sets them apart, as smaller slices will not execute unnecessary
code to compute the values, decreasing the executing time.
\item[Features covered] Which features or language a slicing algorithm
covers. Different approaches to slicing cover different programming
languages and even paradigms. There are slicing techniques (published or
commercially available) for most popular programming languages, from C++
to Erlang. Some slicing techniques only cover a subset of the targeted
language, and as such are less useful for commercial applications, but
can be a stepping stone in the betterment of the field.
\item[Speed] Speed of graph generation and slice creation. As previously
commented, slicing is a two-step process: build a graph and traverse it.
The traversal is linear in most proposals, with small variations. Graph
generation tends to be longer and with higher variance, but it is not as
relevant, because it is only done once (per program being analyzed). As
such, this is the least important metric. Only proposals that deviate
from the aforementioned schema show a wider variation in speed.
\end{description}
\section{Exception handling in Java}
\label{sec:intro-exception}
Exception handling is common in most modern programming languages. In Java, it
consists of the following elements:
\begin{description}
\item[Throwable] An interface that encompasses all the exceptions or errors
that may be thrown. Child classes are \texttt{Exception} for most errors
and \texttt{Error} for internal errors in the Java Virtual Machine.
Exceptions can be classified in two categories: \textsl{unchecked}
(those inheriting from \texttt{RuntimeException} or \texttt{Error}) and
\textsl{checked} (the rest). The first may be thrown anywhere, whereas
the second, if thrown, must be caught or declared in the method header.
\item[throws] A statement that activates an exception, altering the normal
control-flow of the method. If the statement is inside a \textsl{try}
block with a \textsl{catch} clause for its type or any supertype, the
control flow will continue in the first statement of such clause.
Otherwise, the method is exited and the check performed again, until
either the exception is caught or the last method in the stack
(\textsl{main}) is popped, and the execution of the program ends
abruptly.
\item[try] This statement is followed by a block of statements and by one or
more \textsl{catch} clauses. All exceptions thrown in the statements
contained or any methods called will be processed by the list of
catches. Optionally, after the \textsl{catch} clauses a \textsl{finally}
block may appear.
\item[catch] Contains two elements: a variable declaration (the type must be
an exception) and a block of statements to be executed when an exception
of the corresponding type (or a subtype) is thrown. \textsl{catch}
clauses are processed sequentially, and if any matches the type of the
thrown exception, its block is executed, and the rest are ignored.
Variable declarations may be of multiple types \texttt{(T1|T2 exc)},
when two unrelated types of exception must be caught and the same code
executed for both. When there is an inheritance relationship, the parent
suffices.\footnotemark
\item[finally] Contains a block of statements that will always be executed
if the \textsl{try} is entered. It is used to tidy up, for example
closing I/O streams. The \textsl{finally} can be reached in two ways:
with an exception pending (thrown in \textsl{try} and not captured by
any \textsl{catch} or thrown inside a \textsl{catch}) or without it
(when the \textsl{try} or \textsl{catch} block end successfully). After
the last instruction of the block is executed, if there is an exception
pending, control will be passed to the corresponding \textsl{catch} or
the program will end. Otherwise, the execution continues in the next
statement after the \textsl{try-catch-finally} block.
\end{description}
\footnotetext{Introduced in Java 7, see \url{https://docs.oracle.com/javase/7/docs/technotes/guides/language/catch-multiple.html} for more details.}
\subsection{Exception handling in other programming languages}
In almost all programming languages, errors can appear (either through the
developer, the user or the system's fault), and must be dealt with. Most of the
popular object oriented programs feature some kind of error system, normally
very similar to Java's exceptions. In this section, we will perform a small
survey of the error-handling techniques used on the most popular programming
languages. The language list has been extracted from a survey performed by the
programming Q\&A website Stack
Overflow\footnote{\url{https://stackoverflow.com}}. The survey contains a
question about the technologies used by professional developers in their work,
and from that list we have extracted those languages with more than $5\%$ usage
in the industry. Table~\ref{tab:popular-languages} shows the list and its
source. Except Bash, Assembly, VBA, C and G, the rest of the languages shown
feature an exception system similar to the one appearing in Java.
\begin{table}
\begin{minipage}{0.6\linewidth}
\centering
\begin{tabular}{r | r }
\textbf{Language} & $\%$ usage \\ \hline
JavaScript & 69.7 \\ \hline
HTML/CSS & 63.1 \\ \hline
SQL & 56.5 \\ \hline
Python & 39.4 \\ \hline
Java & 39.2 \\ \hline
Bash/Shell/PowerShell & 37.9 \\ \hline
C\# & 31.9 \\ \hline
PHP & 25.8 \\ \hline
TypeScript & 23.5 \\ \hline
C++ & 20.4 \\ \hline
\end{tabular}
\end{minipage}
\begin{minipage}{0.39\linewidth}
\begin{tabular}{r | r }
\textbf{Language} & $\%$ usage \\ \hline
C & 17.3 \\ \hline
Ruby & 8.9 \\ \hline
Go & 8.8 \\ \hline
Swift & 6.8 \\ \hline
Kotlin & 6.6 \\ \hline
R & 5.6 \\ \hline
VBA & 5.5 \\ \hline
Objective-C & 5.2 \\ \hline
Assembly & 5.0 \\ \hline
\end{tabular}
\end{minipage}
% The caption has a weird structure due to the fact that there's a footnote
% inside of it.
\caption[Commonly used programming languages]{The most commonly used
programming languages by professional developers\protect\footnotemark}
\label{tab:popular-languages}
\end{table}
\footnotetext{Data from \url{https://insights.stackoverflow.com/survey/2019/\#technology-\_-programming-scripting-and-markup-languages}}
The exception systems that are similar to Java are mostly all the same,
featuring a \texttt{throw} statement (\texttt{raise} in Python), try-catching
structure and most include a finally block that may be appended to try blocks.
The difference resides in the value passed by the exception, which in languages
that feature inheritance it is a class descending from a generic error or
exception, and in languages without it, it is an arbitrary value (e.g.
JavaScript, TypeScript). In object--oriented programming, the filtering is
performed by comparing if the exception is a subtype of the exception being
caught (Java, C++, C\#, PowerShell\footnotemark, etc.); and in languages with
arbitrary exception values, a boolean condition is specified, and the first
catch block that fulfills its condition is activated, in following a pattern
similar to that of \texttt{switch} statements (e.g. JavaScript). In both cases
there exists a way to indicate that all exceptions should be caught, regardless
of type and content.
\footnotetext{Only since version 2.0, released with Windows 7.}
On the other hand, in the other languages there exist a variety of systems that
emulate or replace exception handling:
\begin{description} % bash, vba, C and Go exceptions explained
\item[Bash] The popular Bourne Again SHell features no exception system, apart
from the user's ability to parse the return code from the last statement
executed. Traps can also be used to capture erroneous states and tidy up all
files and environment variables before exiting the program. Traps allow the
programmer to react to a user or system--sent signal, or an exit run from
within the Bash environment. When a trap is activated, its code run, and the
signal doesn't proceed and stop the program. This doesn't replace a fully
featured exception system, but \texttt{bash} programs tend to be small in
size, with programmers preferring the efficiency of C or the commodities of
other high--level languages when the task requires it.
\item[VBA] Visual Basic for Applications is a scripting programming language
based on Visual Basic that is integrated into Microsoft Office to automate
small tasks, such as generating documents from templates, making advanced
computations that are impossible or slower with spreadsheet functions, etc.
The only error--correcting system it has is the directive \texttt{On Error
$x$}, where $x$ can be 0 ---lets the error crash the program---,
\texttt{Next} ---continues the execution as if nothing had happened--- or a
label in the program ---the execution jumps to the label in case of
error. The directive can be set and reset multiple times, therefore creating
artificial \texttt{try-catch} blocks, but there is no possibility of
attaching a value to the error, lowering its usefulness.
\item[C] In C, errors can also be control via return values, but some of the
instructions it features can be used to create a simple exception system.
\texttt{setjmp} and \texttt{longjmp} are two instructions which set up and
perform inter--function jumps. The first makes a snapshot of the call stack
in a buffer, and the second returns to the position where the buffer was
safe, destroying the current state of the stack and replacing it with the
snapshot. Then, the execution continues from the evaluation of
\texttt{setjmp}, which returns the second argument passed to
\texttt{longjmp}. An example can be seen in figure~\ref{fig:exceptions-c},
where line 2 of the \texttt{main} function will be executed twice, once when
it is normally run (returning 0) and the second when line 3 in
\texttt{safe\_sqrt} is run, returning the second argument of line 3, and
therefore entering the else block in the \texttt{main} method.
\item[Go] The programming language Go is the odd one out in this section, being a
modern programming language without exceptions, though it is an intentional
design decision made by its authors\footnotemark. The argument made was that
exception handling systems introduce abnormal control--flow and complicate
code analysis and clean code generation, as it is not clear the paths that
the code may follow. Instead, Go allows functions to return multiple values,
with the second value typically associated to an error type. The error is
checked before the value, and acted upon. Additionally, Go also features a
simple panic system, with the functions \texttt{panic} ---throws an
exception with a value associated---, \texttt{defer} ---runs after the
function has ended or when a \texttt{panic} has been activated--- and
\texttt{recover} ---stops the panic state and retrieves its value. The
\texttt{defer} statement doubles as catch and finally, and multiple
instances can be accumulated. When appropriate, they will run in LIFO order
(Last In--First Out).
Then, the exception \carlos{complete}
\end{description}
\footnotetext{\url{https://golang.org/doc/faq\#exceptions}}
\begin{figure} % example of exception system in C
\centering
\begin{minipage}{0.5\linewidth}
\begin{lstlisting}[language=C]
int main() {
if (!setjmp(ref)) {
res = safe_sqrt(x, ref);
} else {
// Handle error
printf /* ... */
}
}
\end{lstlisting}
\end{minipage}
\begin{minipage}{0.49\linewidth}
\begin{lstlisting}[language=C]
double safe_sqrt(double x, int ref) {
if (x < 0)
longjmp(ref, 1);
return /* ... */;
}
\end{lstlisting}
\end{minipage}
\caption{A user-created exception system in C}
\label{fig:exceptions-c}
\end{figure}
% vim: set noexpandtab:tabstop=2:shiftwidth=2:softtabstop=2:wrap

126
motivation.tex
View File

@ -1,126 +0,0 @@
% !TEX encoding = UTF-8
% !TEX spellcheck = en_GB
% !TEX root = paper.tex
\chapter{Introduction}
\label{cha:introduction}
\section{Motivation}
\label{sec:motivation}
Program slicing~\cite{Wei81} is a debugging technique which, given a line of
code and a variable of a program, simplifies such program so that the only parts
left of it are those that affect the value of the selected variable.
\begin{example}[Program slicing in a simple method]
If the following program is sliced on line 5 (variable \texttt{x}), the
result would be the program of the right, with the \texttt{if} block
skipped, as it doesn't affect the value of \texttt{x}.
\label{exa:program-slicing}
\begin{center}
\begin{minipage}{0.49\linewidth}
\begin{lstlisting}[stepnumber=1]
void f(int x) {
if (x < 0)
System.err.println(x);
x++;
System.out.println(x);
}
\end{lstlisting}
\end{minipage}
\begin{minipage}{0.49\linewidth}
\begin{lstlisting}[stepnumber=1]
void f(int x) {
x++;
System.out.println(x);
}
\end{lstlisting}
\end{minipage}
\end{center}
\end{example}
Slices are an executable program whose execution will produce the same values
for the specified line and variable as the original program, and are used to
facilitate debugging of large and complex programs, where the data flow may not
be easily understandable.
Though it may seem a really powerful technique, the whole Java language is not
completely covered by it, and that makes it difficult to apply in practical
settings. An area that has been investigated, yet doesn't have a definitive
solution yet is exception handling. Example~\ref{exa:program-slicing2}
demonstrates how, even using the latest developments in program
slicing~\cite{allen03}, the sliced version doesn't include the catch block, and
therefore doesn't produce a correct slice.
\begin{example}[Program slicing with examples]
If the following program is sliced in line 17, variable \texttt{x}, the
slice is incomplete, as it lacks the \texttt{catch} block from lines 4-6.
\label{exa:program-slicing2}
\begin{center}
\begin{minipage}{0.49\linewidth}
\begin{lstlisting}[stepnumber=1]
void f(int x) {
try {
g(x);
} catch (RuntimeException e) {
System.err.println("Error");
}
System.out.println("g() was ok");
g(x);
}
void g(int x) {
if (x < 0) {
throw new RuntimeException();
}
System.out.println(x);
}
\end{lstlisting}
\end{minipage}
\begin{minipage}{0.49\linewidth}
\begin{lstlisting}[stepnumber=1]
void f(int x) {
try {
g(x);
}
g(x);
}
void g(int x) {
if (x < 0) {
throw new RuntimeException();
}
System.out.println(x);
}
\end{lstlisting}
\end{minipage}
\end{center}
\end{example}
\carlos{completar}
\section{Contributions}
The main contribution of this paper is a complete solution for program slicing
in the presence of exception handling constructs for Java; but in the process we
will present a history of program slicing, specifically those changes that
have affected exception handling. Furthermore, we provide a summary of the
different contributions each author has made to the field.
The rest of the paper is structured as follows: chapter~\ref{cha:background}
summarizes the theoretical background required, chapter~\ref{cha:state-art}
provides a bird's eye view of the current state of the art,
chapter~\ref{cha:solution} provides a step by step description of the problems
found with the state of the art and the solutions proposed, and
chapter~\ref{cha:conclusion} summarizes the paper and provides avenues of future
work.
% vim: set noexpandtab:tabstop=2:shiftwidth=2:softtabstop=2:wrap

100
paper.tex
View File

@ -1,100 +0,0 @@
% !TEX encoding = UTF-8
% !TEX spellcheck = en_GB
% !TEX root = paper.tex
\documentclass[a4paper,twoside]{report}
\usepackage[spanish,english]{babel}
\usepackage[utf8]{inputenc}
\usepackage{listings}
\usepackage{algorithm}
\usepackage{algorithmic}
\renewcommand{\algorithmicrequire}{\textbf{Input:}}
\renewcommand{\algorithmicensure}{\textbf{Output:}}
\usepackage{amsthm}
\usepackage{amssymb}
\theoremstyle{definition}
\newtheorem{definition}{Definition}
\newtheorem{example}{Example}
\usepackage{hyperref}
\usepackage{graphics}
\usepackage{title/mitssTitle}
\newcommand{\ctrldep}{\rightarrow^{ctrl}}
\newcommand{\datadep}{\rightarrow^{data}}
\usepackage{todonotes}
\usepackage{marginnote}
\newif\ifpaperVersion
%\paperVersiontrue
\paperVersionfalse
\ifpaperVersion
% Paper version
\newcommand{\ignore}[1]{}
\newcommand{\deleted}[1]{}
\newcommand{\added}[1]{#1}
\newcommand{\pending}[1]{}
\newcommand{\done}[1]{}
\newcommand{\doubt}[1]{}
\newcommand{\josep}[1]{}
\newcommand{\carlos}[1]{}
\newcommand{\sergio}[1]{}
\else
% Working
\definecolor{ignoreColor}{rgb}{1,0.5,0}
\definecolor{pendingColor}{rgb}{0.2,0.7,0.2}
\definecolor{doneColor}{rgb}{0.7,0.2,0.7}
\definecolor{doubtColor}{rgb}{0.6,0.6,0.4}
\definecolor{josepColor}{rgb}{0.2,0.6,0.6}
\definecolor{carlosColor}{rgb}{0.6,0.2,0.6}
\definecolor{sergioColor}{rgb}{1.0,0.5,0.0}
\newcommand{\ignore}[1]{\textcolor{ignoreColor}{\#Ignored: #1}}
\newcommand{\deleted}[1]{\textcolor{red}{\#Deleted: #1}}
\newcommand{\added}[1]{\textcolor{blue}{\#Added: #1}}
\newcommand{\pending}[1]{\textcolor{pendingColor}{\#Pending: #1}}
\newcommand{\done}[1]{\textcolor{doneColor}{\#Done: #1}}
\newcommand{\doubt}[1]{\textcolor{doubtColor}{\#Doubt: #1}}
\newcommand{\josep}[1]{\textcolor{josepColor}{\#JJJ: #1}}
\newcommand{\carlos}[1]{\textcolor{carlosColor}{\#CCC: #1}}
\newcommand{\sergio}[1]{\textcolor{sergioColor}{\#SSS: #1}}
\fi
\title{Fragmentación de programas con excepciones}
%\title{Program slicing with exceptions}
\author{Carlos S. Galindo Jiménez}
\date{diciembre de 2019}
\supervisor{Josep Francesc Silva Galiana}
\curso{2019-2020}
\begin{document}
\algsetup{linenodelimiter=.}
\include{listings-config}
\maketitle
\begin{abstract}
\carlos{por completar}
\end{abstract}
\selectlanguage{spanish}
\begin{abstract}
\carlos{por completar}
\end{abstract}
\selectlanguage{english}
\tableofcontents
\include{Secciones/motivation}
\include{Secciones/background}
\include{Secciones/incremental_slicing}
\include{Secciones/problem_solution}
\include{Secciones/state_of_the_art}
\include{Secciones/conclusion}
\bibliographystyle{plain}
\bibliography{../../../../../../Biblio/biblio.bib}
\end{document}
% vim: set noexpandtab:ts=2:sw=2:wrap

112
solution.tex
View File

@ -1,112 +0,0 @@
% !TEX encoding = UTF-8
% !TEX spellcheck = en_GB
% !TEX root = paper.tex
\chapter{Proposed solution}
This solution is an extension of Allen's\cite{AllH03}, with some modifications to solve the problem found. Before starting, we need to split all instructions in three categories:
\begin{description}
\item[statement] non-branching instruction, e.g. an assignment or method call.
\item[predicate] conditional branch, e.g. if statements and loops.
\item[pseudo-predicate] unconditional jump, e.g. break, continue, return, goto and throw instructions.
\end{description}
Pseudo-predicates have been previously use to model unconditional jumps with a counter-intuitive reasoning: the next statement that would be executed were the pseudo-predicate not there would be executed, therefore it is control dependent on it. Going back to the definition of control dependency, one could argue that the real control dependency is on the conditional branch that lead to the
\begin{figure}
\centering
\begin{lstlisting}
if (a) {
return a;
}
print(a);
\end{lstlisting}
\begin{lstlisting}
if (a) {
}
print(a);
\end{lstlisting}
\caption{Example of pseudo-predicates control dependencies}
\end{figure}
This is the process used to build the Program Dependence Graph.
\begin{description}
\item[Step 1 (static analysis):] Identify for each instruction the variables read and defined. Each method is annotated with the global variables that they access or modify.
\item[Step 2 (build CFGs):] Build a CFG for each method of the program. The start of all methods is a vertex labeled \textsl{enter}, which also contains the assignments for parameters and global variables used (\texttt{var = var\_in}). The \textsl{enter} node is connected to the first instruction of the method. In a similar fashion, all methods end in an \textsl{exit} vertex with the corresponding output variables. There exists one \textsl{normal exit} to which the last instruction and all return instructions are connected. If the method can throw any exceptions, there exists one \textsl{error exit} for each type of exception that may be thrown. The normal and erroneous exits are connected to the \textsl{exit} node.
Every normal statement is connected to the subsequent one by an unlabeled edge. Predicates have two outgoing edges, labeled \textsl{true} and \textsl{false}. Pseudo-predicates also have two outgoing edges. The \textsl{true} edge is connected to the destination of the jump (\textsl{normal exit} in the case of return, the begin or end of the loop in the case of continue and break, etc.). The \textsl{false} edge is a non-executable edge, marked with a dashed line, and it is connected to the next instruction that would be executed if the pseudo-predicate was a \textsl{nop}.
Nodes that represent a call to a method $M$ include the transfer of parameters and variables that may be read or written to, then execute the call, and finally the extraction of modified variables. Call nodes are an exception to the previous paragraph, as they can have an unlimited amount of outgoing edges. Each outgoing edge lands on a pseudo-predicate which indicates if the execution was correct or an exception was raised. The executable edge of each pseudo-predicate will lead to the next instruction to be executed, whereas the non-executable one will lead to the end of the try-catch block. All call nodes can lead to a \textsl{normal return} node, which is linked to the next instruction, and one error node for each type of exception that may be thrown. The erroneous returns are labeled \textsl{catch ExType}, and lead to the first instruction in the corresponding catch block\footnotemark. Any exception that may not be caught will lead to the erroneous exit node of the method it's in. See the example for more details.
\footnotetext{A problem presents itself here, as some exceptions may be able to trigger different catch blocks, due to the secuential nature of catches and polymorphism in Java. A way to fix this is to make catch blocks behave as a switch.}. %TODO
\item[Step 3 (compute dependences):] For each node in the CFG, compute the control and data dependencies. Non-executable edges are only included when computing control dependencies.\\
\carlos{put inside definition}
A node $a$ is \textsl{control dependent} on node $b$ iff $a$ post-dominates one but not all of $b$'s successors.\\
A node $a$ is \textsl{data dependent} on node $b$ iff $b$ defines or may define a variable $x$, $a$ uses or may use $x$, and there is an $x$-definition-free path in the CFG from $b$ to $a$.\\
\item[Step 4 (convert each CFG into a PDG):] each node of the CFG is one node of the PDG, with two exceptions. The first are the \textsl{enter}, \textsl{exit} and method call nodes, where the variable input and output assignments are split and placed as control-dependent on their original node. The second is the \textsl{exit} node, which is to be removed (the control-dependencies from \textsl{exit} to the variable outputs is transferred to the \textsl{enter} node). Then all the dependencies computed in the previous step are drawn.
\item[Step 5 (connect PDGs to form a SDG):] each method call to $M$ must be connected to the \textsl{enter} node in $M$'s PDG, as a control dependence. Each variable input from the method call is connected to a variable input of the method definition via a data dependence. Each variable output from the method definition is connected to the variable output of the method call via a data dependence. Each method exit is connected \carlos{complete}.
\end{description}
\begin{itemize}
\item An extra type of control dependency represented by an ``exception edge''. It will represent the need to include a \textsl{catch} clause when an exception can be thrown. It is represented with a dotted line (dashed line is for data dependency). These edges have a special characteristic: when one is traversed, only ``exception edges'' may be traversed from the new nodes included in the slice. If the same node is reached by another kind of edge, the restriction is lifted. The behavior is documented in algorithm \ref{alg:2pass}, with changes from the original algorithm are \underline{underlined}.
\item Add an extra ``exception edge'' from each ``exit with exception of type T'' node, where the type of the exception is \texttt{t} to all the corresponding ``\texttt{throw e}'', such that \texttt{e} is or inherits from \texttt{T}.
\item Add an extra ``exception edge'' from each catch statement to every statement that can throw that error.
\item The exception edges will only be placed when the method or the try-catch statement are loop-carrier\footnote{Loop-carrier, when referring to a statement, is the property that in a CFG for the complete program, the node representing the statement is part of a loop, meaning that it could be executed again once it is executed.}.
\end{itemize}
\begin{algorithm} % generate slice
\caption{Two-pass algorithm to obtain a backward static slice with exceptions}
\label{alg:2pass}
\begin{algorithmic}[1]
\REQUIRE SDG $\mathcal{G}$ representing program P. $\mathcal{G} = \{\mathcal{S}, \mathcal{E}\}$, where $\mathcal{S}$ is a set of states (some are statements) connected by a set of edges $\mathcal{E}$. Each edge, is a triplet composed of the type of edge (control, data or \underline{exception} dependency, summary, param-in, param-out), the source and destination of the edge.
\REQUIRE A slicing criterion, composed of a statement $s \in \mathcal{S}$ and a variable $v$.
\ENSURE $\mathcal{S}' \subseteq \mathcal{S}$, representing the slice of P according to the criterion provided.
\medskip
\COMMENT{First pass (do not traverse output parameter edges).}
\STATE{$\mathcal{S}' \Leftarrow \emptyset$ (slice), $\mathcal{Q}\Leftarrow\{s\}$ (queue), $\mathcal{S}\Leftarrow \mathcal{S} - \{s\}$ (not visited), $\mathcal{R}\Leftarrow \emptyset$ (only visited via exception edge)}
\WHILE{$\mathcal{Q} \neq \emptyset$}
\STATE{$a \in \mathcal{Q}$} \COMMENT{Select an element from $\mathcal{Q}$}
\STATE{$\mathcal{Q} \Leftarrow \mathcal{Q} - \{a\}$}
\STATE{$\mathcal{S}' \Leftarrow \mathcal{S}' + \{a\}$}
\FORALL{$\mathcal{A}$ in $\{\{type, origin, a\} \in \mathcal{E}\}$}
\IF{$type \neq$ param-out \AND ($origin \notin \mathcal{S}'$ \OR ($origin \in \mathcal{R}$ \AND $a \notin \mathcal{R}$))} \label{line:param-out}
\IF{\underline{$a \in \mathcal{R}$}}
\IF{\underline{$type =$ exception}}
\STATE{\underline{$\mathcal{Q} \Leftarrow \mathcal{Q} + \{origin\}$}}
\STATE{\underline{$\mathcal{R} \Leftarrow \mathcal{R} + \{origin\}$}}
\ENDIF
\ELSE
\STATE{$\mathcal{Q} \Leftarrow \mathcal{Q} + \{origin\}$}
\ENDIF
\ENDIF
\ENDFOR
\ENDWHILE
\\
\medskip
\COMMENT{Second pass (very similar, do not traverse input parameter edges).}
\STATE $\mathcal{Q} \Leftarrow \mathcal{S}'$
\WHILE{$\mathcal{Q} \neq \emptyset$}
\STATE{$a \in \mathcal{Q}$} \COMMENT{Select an element from $\mathcal{Q}$}
\STATE{$\mathcal{Q} \Leftarrow \mathcal{Q} - \{a\}$}
\STATE{$\mathcal{S}' \Leftarrow \mathcal{S}' + \{a\}$}
\FORALL{$\mathcal{A}$ in $\{\{type, origin, a\} \in \mathcal{E}\}$}
\IF{$type \neq$ param-in \AND ($origin \notin \mathcal{S}'$ \OR ($origin \in \mathcal{R}$ \AND $a \notin \mathcal{R}$))}
\IF{\underline{$a \in \mathcal{R}$}}
\IF{\underline{$type =$ exception}}
\STATE{\underline{$\mathcal{Q} \Leftarrow \mathcal{Q} + \{origin\}$}}
\STATE{\underline{$\mathcal{R} \Leftarrow \mathcal{R} + \{origin\}$}}
\ENDIF
\ELSE
\STATE{$\mathcal{Q} \Leftarrow \mathcal{Q} + \{origin\}$}
\ENDIF
\ENDIF
\ENDFOR
\ENDWHILE
\end{algorithmic}
\end{algorithm}
% vim: set noexpandtab:ts=2:sw=2:wrap

69
state_of_the_art.tex
View File

@ -1,69 +0,0 @@
% !TEX encoding = UTF-8
% !TEX spellcheck = en_GB
% !TEX root = paper.tex
\chapter{State of the art}
Slicing was proposed\cite{Wei81} and improved until the proposal of the current system (the SDG) \carlos{(citation)}. Specifically in the context of exceptions, multiple approaches have been attempted, with varying degrees of success. There exist commercial solutions for various programming languages: \carlos{name them and link}.
In the realm of academia, there exists no definite solution. One of the most relevant initial proposal\cite{AllH03}, although not the first one\cite{SinH98,SinHR99} to target Java specifically.
It uses the existing proposals for \textsl{return}, \textsl{goto} and other unconditional jumps to model the behavior of \textsl{throw} statements. Control flow inside \textsl{try-catch-finally} statements is simulated, both for explicit \textsl{throw} and those nested inside a method call. The base algorithm is presented, and then the proposal is detailed as changes. Unchecked exceptions are considered but regarded as ``worthless'' to include, due to the increase in size of the slices, which reduces their effectiveness as a debugging tool. This is due to the number of unchecked exceptions embedded in normal Java instructions, such as \texttt{NullException} in any instance field or method, \texttt{IndexOutOfBoundsException} in array accesses and countless others. On top of that, handling \textsl{unchecked} exceptions opens the problem of calling an API to which there is no analyzable source code, either because the module was compiled before-hand or because it is part of a distributed system. The first should not be an obstacle, as class files can be easily decompiled. The only information that may be lost is variable names and comments, which don't affect a slice's precision, only its readability.
Chang and Jo\cite{JoC04} present an alternative to the CFG by computing exception-induced control flow separately from the traditional control flow computation, but go no further into the ramifications it entails for the PDG and the SDG.
Jiang et al.\cite{JiaZSJ06} describes a solution specific for the exception system in C++, which differs from Java's implementation of exceptions. They reuse the idea of non-executable edges in \textsl{throw} nodes, and introduce handling \textsl{catch} nodes as a switch, each trying to catch the exception before deferring onto the next \textsl{catch} or propagating it to the calling method. Their proposal is center around the IECFG (Improved Exception Control-Flow Graph), which propagates control dependencies onto the PDG and then the SDG. Finally, in their SDG, each normal and exceptional return and their data output are connected to all \textsl{catch} statements where the data may have arrived, which is fine for the example they propose, but could be inefficient if the method has many different call nodes.
Others\cite{PraMB11} have worked specifically on the C++ exception framework. \carlos{remove or expand}.
Finally, Hao\cite{JieS11} introduced a Object-Oriented System Dependence Graph with exception handling (EOSDG), which represented a generic object-oriented language, with exception handling capabilities. Its broadness allows for the EOSDG to fit into both Java and C++. It uses concepts from Jiang\cite{JiaZSJ06}, such as cascading \textsl{catch} statements, while adding explicit support for virtual calls, polymorphism and inheritance.
% TODO UNCOMPLETE
\hrulefill
\marginnote{Alternative explanation of \cite{AllH03}, with counter example. Maybe should move the counter example backwards.}
In her paper, Horwitz suggests treating exceptions in the following way:
\begin{itemize}
\item Statements are divided into statements, predicates (loops and conditional blocks) and pseudo-predicates (return and throw statements). Statements only have one successor in the CFG, predicates have two (one when the condition is true and another when false), pseudo-predicates have two, but the one labeled ``false'' is non-executable. The non-executable edge connects to the statement that would be executed if the unconditional jump was replaced by a ``nop''.
\item \textsl{try-catch-finally} blocks are treated differently, but it has fewer dependencies than needed. Each catch block is control-dependent on any statement that may throw the corresponding exception. The
\end{itemize}
\begin{lstlisting}[title=Example]
void main() {
int x = 0;
while (true) {
try {
f(x);
} catch (ExceptionA e) {
x--;
} catch (ExceptionB e) {
System.err.println(x);
} catch (ExceptionC e) {
System.out.println(x);
}
System.out.println(x);
}
}
void f(x) {
x--;
if (x > 10)
throw new ExceptionA();
else if (x == 0)
throw new ExceptionB();
else if (x > 0)
throw new ExceptionC();
x++;
System.out.println(x);
}
static class ExceptionA extends ExceptionC {}
static class ExceptionB extends Exception {}
static class ExceptionC extends Exception {}
\end{lstlisting}
In this example we can explore all the errors found with the current state of the art.
The first problem found is the lack of \texttt{catch} statements in the slice, as no edge is drawn from the catch. Some of the catch blocks will be included via data dependencies, but some may not be reached, though they are still necessary if the slice includes anything after a caught exception.
Therefore, an extra control dependency must be introduced, in order to always include a ``catch'' statement in the slice if the ``throw'' statement is in the slice. In the example, only the catch statement from line 20 will be included, and if ExceptionC or ExceptionB were thrown, they would not be caught. That would not be a problem if the function $f$ was not executed again, but it is, making the slice incorrect.
% vim: set noexpandtab:ts=2:sw=2:wrap