Small changes

Chapters/Chapter01.tex

@@ -2,26 +2,26 @@
 \chapter{Introduction}\label{ch:introduction}
 % ************************************************
 
-During the last decades, the area of solving \emph{propositinal
-  satisfiability} (\sat)~\cite{DP09} and consequently the related area
-of solving \emph{satisfiability modulo theories} (\smt)~\cite{BSST09}
-has undergone steep development in both theory and practice. Achieved
-advances of \smt solving opened new research directions in program
-analysis and verification, where \smt solvers are now seen as standard
-tools.
+During the last decades, the area \emph{satisfiability modulo
+  theories} (\smt)~\cite{BSST09} has undergone steep development in
+both theory and practice. Achieved advances of \smt solving opened new
+research directions in program analysis and verification, where \smt
+solvers are now seen as standard tools.
 
-The task for an \smt solver is for a given first-order formula in a
+The task of an \smt solver is for a given first-order formula in a
 given first-order theory decide, whether the formula is
 satisfiable. Usually, if the formula is satisfiable, the \smt solver
 also has the ability to provide its model. Modern \smt solvers support
-wide range of different first-order theories -- for example, theories
+wide range of different first-order theories -- for example theories
 of integers, real numbers, floating-point numbers, arrays, strings,
-inductively defined data types, bit-vectors and various combinations
-and framgents of these theories. From the software analysis and
+inductively defined data types, bit-vectors, and various combinations
+and sub-theories of these theories. From the software analysis and
 verification point of view, a particularly important of these theories
-is the theory of bit-vectors, which can be used to describing
-properties of computer programs, since they usually use data-types of
-bounded size instead of mathematical integers.
+is the theory of bit-vectors, which can be used to describe properties
+of computer programs, since programs usually use data-types of bounded
+size instead of mathematical integers. Additionally, operations over
+these bounded data-types naturally corespond to operations of the
+bit-vector theory.
 
 The benefit of describing properties of programs by bit-vector
 formulas is twofold. Formulas in the bit-vector theory allow to model
@@ -36,25 +36,26 @@ circuits, static analysis, or test generation. Most of the current
 \smt solvers for the quantifier-free bit-vector formulas eagerly or
 lazily translate the formula to the propositional logic
 (\emph{bit-blasting}) and use an efficient \sat solver to decide its
-satisfiability. Therefore, the efficiency of most of the \smt solvers
-for such formulas is tightly connected to the efficiency of the \sat
+satisfiability. Therefore, the efficiency of most of the bit-vector
+\smt solvers is tightly connected to the efficiency of the \sat
 solvers. Plenty of solvers for the quantifier-free bit-vector formulas
 exist: Beaver~\cite{Beaver}, Boolector~\cite{Boolector},
 CVC4~\cite{CVC4}, MathSAT5~\cite{MathSAT}, OpenSMT~\cite{OpenSMT},
 Sonolar~\cite{Sonolar}, Spear~\cite{Spear}, STP~\cite{STP},
-UCLID~\cite{LS04}, Yices~\cite{Yices}, or Z3~\cite{Z3}.
+UCLID~\cite{LS04}, Yices~\cite{Yices}, and Z3~\cite{Z3}.
 
 In some cases, quantifier-free formulas are not succint enough and
-quantified formulas are necessary. Bit-vector quantified formulas
-arise naturally for example in applications that generate loop
-invariants, ranking functions, loop summaries, or that test equality
-of two symbolic states. However, the \smt solvers' support of
-quantified bit-vector logic is much more modest -- CVC4, Yices, and Z3
-officially support quantifiers in bit-vector formulas. Recently,
-quantifiers have been also implemented in an development version of
-Boolector. All of these \smt solvers solve quantified bit-vector
-formulas by some variant of quantifier-instantiation and using a
-solver for quantifier-free formulas as an oracle.
+quantified formulas are necessary. Quantified bit-vector formulas
+arise naturally for example in applications that need test equality of
+two symbolically represented states, or applicatichch that generate
+loop invariants, ranking functions or loop summaries. However, the
+\smt solvers' support of quantified bit-vector logic is much more
+modest -- CVC4, Yices, and Z3 officially support quantifiers in
+bit-vector formulas. Recently, quantifiers have been also implemented
+in an development version of Boolector. All of these \smt solvers
+solve quantified bit-vector formulas by some variant of
+quantifier-instantiation and using a solver for quantifier-free
+formulas as an oracle.
 
 In the last year, we have proposed a different approach. We have
 implemented a symbolic solver Q3B, which is based on binary decision
@@ -68,23 +69,23 @@ bit-vectors, which combines symbolic representation by \bdds with
 search techniques employed by existing state-of-the-art solvers. I
 also plan to continue developing the symbolic solver Q3B itself,
 namely improving its efficiency and adding support for features as
-uninterpreted functions and arrays that are important in the software
+uninterpreted functions and arrays, which are important in the software
 verification.
 
 The thesis proposal is organized as follows. Chapter~\ref{ch:sota}
 summarizes the state of the art and is divided into six sections. The
 first section introduces necessary background and notations from
 propositional logic and first-order logic. The second section
-describes approaches to solving propositional satisfiability problem
-and the third section describes approaches to solving satisfiability
-modulo theories. The fourth and fifth sections are devoted to solving
+describes approaches to solving propositional satisfiability and the
+third section describes approaches to solving satisfiability modulo
+theories. The fourth and fifth sections are devoted to solving
 quantifier-free and quantifed formulas over the theory of bit-vectors,
-respectively. The final, sixth, section describes results about the
-computational complexity of bit-vector
+respectively. The final, sixth, section describes results concerning
+the computational complexity of bit-vector
 logics. Chapter~\ref{ch:achieved} describes results, which we have
 achieved during the first two years of my PhD
 study. Chapter~\ref{ch:aims} presents the aim of the thesis and states
-plans remaining part of the PhD study.
+plans for the remaining part of my PhD study.
 
 %%% Local Variables:
 %%% mode: latex

FrontBackmatter/Titlepage.tex

@@ -23,7 +23,7 @@
 
         \vfill
 
-        \mySubtitle \\
+        \spacedlowsmallcaps{\mySubtitle} \\
         %\myDegree \\
         %\myDepartment \\
         \smallskip
@@ -33,7 +33,9 @@
         \vfill
 
       \end{center}
-      \noindent \myFaculty, \myUni \\
-      \noindent Supervisor: \myProf
+      \begin{tabularx}{\linewidth}{l X r}
+        \myFaculty & & \spacedlowsmallcaps{Supervisor}  \\
+        \myUni & & \myProf
+      \end{tabularx}
   \end{addmargin}
 \end{titlepage}

classicthesis-config.tex

@@ -42,7 +42,7 @@
 % ****************************************************************************************************
 % 2. Personal data and user ad-hoc commands
 % ****************************************************************************************************
-\newcommand{\myTitle}{SMT Solving Bit-Vector Formulas\xspace}
+\newcommand{\myTitle}{SMT Solving for the Theory of Bit-Vectors\xspace}
 \newcommand{\mySubtitle}{PhD Thesis Proposal\xspace}
 %\newcommand{\myDegree}{Doktor-Ingenieur (Dr.-Ing.)\xspace}
 \newcommand{\myName}{Martin Jonáš\xspace}