From 83e5ff1a011783be60d8725f1a340369311d9ec2 Mon Sep 17 00:00:00 2001
From: Marcin Chrzanowski <mc370754@students.mimuw.edu.pl>
Date: Tue, 3 Aug 2021 18:08:54 +0200
Subject: Initial commit

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+% dodaj opcję [licencjacka] dla pracy licencjackiej
+% dodaj opcję [en] dla wersji angielskiej (mogą być obie: [licencjacka,en])
+\documentclass[en]{pracamgr}
+
+% Dane magistranta:
+\autor{Marcin Chrzanowski}{370754}
+
+\title{MSO Query Answering on Trees}
+\titlepl{Odpowiadanie na zapytania MSO na drzewach}
+\kierunek{Computer Science}
+
+% Praca wykonana pod kierunkiem:
+% (podać tytuł/stopień imię i nazwisko opiekuna
+% Instytut
+% ew. Wydział ew. Uczelnia (jeżeli nie MIM UW))
+\opiekun{dr hab. Szymon Toruńczyk\\
+  Institute of Informatics\\
+  }
+
+% miesiąc i~rok:
+\date{August 2021}
+
+%Podać dziedzinę wg klasyfikacji Socrates-Erasmus:
+\dziedzina{
+%11.0 Matematyka, Informatyka:\\
+%11.1 Matematyka\\
+% 11.2 Statystyka\\
+11.3 Informatyka\\
+%11.4 Sztuczna inteligencja\\
+%11.5 Nauki aktuarialne\\
+%11.9 Inne nauki matematyczne i informatyczne
+}
+
+%Klasyfikacja tematyczna wedlug AMS (matematyka) lub ACM (informatyka)
+\klasyfikacja{% TODO
+  D. Software\\
+  D.127. Blabalgorithms\\
+  D.127.6. Numerical blabalysis}
+
+% Słowa kluczowe:
+\keywords{MSO, query answering, trees, finite state automata, tree automata}
+
+% Tu jest dobre miejsce na Twoje własne makra i~środowiska:
+\newtheorem{defi}{Definicja}[section]
+
+% koniec definicji
+
+\begin{document}
+\maketitle
+
+%tu idzie streszczenie na strone poczatkowa
+\begin{abstract}
+    % TODO
+\end{abstract}
+
+\tableofcontents
+%\listoffigures
+%\listoftables
+
+\chapter*{Introduction}
+\addcontentsline{toc}{chapter}{Introduction}
+
+\chapter{Preliminaries}\label{r:pojecia}
+
+% \begin{quote}
+  % Blaba, który jest blaba, nie jest prawdziwym blaba.
+
+% \raggedleft\slshape tłum. z~chińskiego Robert Blarbarucki
+% \end{quote}
+
+\section{Definitions}
+
+\chapter{Branch Infix Regular Queries}\label{r:branchinfix}
+
+\section{Word infix regular queries}
+
+There is a simple and well-known data structure that, given a fixed automaton
+$A$, preprocesses an input word $w$ in time $O(n)$, and afterwords is able to
+answer in time $O(1)$ questions of the form ``Is the infix $w[i, j]$ accepted by
+$A$?''. We present the full construction as we will be generalizing its
+internals for the tree case.
+
+Suppose $A$ is deterministic. We begin by replacing each letter of $w$ with the
+set of states of $A$, $Q$.
+
+Each letter $a$ of $w$ defines an injective function on $Q$, and we draw these
+functions as directed edges between successive copies of $Q$. For example, if
+$A$ in state $q$, reading $a$, would move to state $q'$, then, for any copy of
+$Q$ corresponding to an instance of $a$ in the original word, there will be an
+edge from $q$ there to $q'$ in the successive copy of $Q$.
+
+Now we will color the vertices of the graph we just constructed with the colors
+$1, 2, \ldots, |Q|$ in such a way that
+
+\begin{enumerate}
+    \item every copy of $Q$ has one vertex of each of the $|Q|$ colors;
+    \item when a vertex of color $i$ has an edge to a vertex of color $j$ in a
+        successive copy of $Q$, then $i \geq j$.
+\end{enumerate}
+
+The second point basically means that we will be trying to draw single-color
+paths, but when paths need to join, it is the higher-colored path that gets cut
+off.
+
+The construction is as follows:
+
+\begin{enumerate}
+    \item Color an arbitrary vertex of the first copy of $Q$ with the color $1$.
+    \item Follow the deterministic edges to the end of the word, coloring all
+        vertices along this path with $1$.
+    \item Now color another uncolored vertex of the first copy of $Q$ with the
+        color $2$.
+    \item Try following edges as far as possible, coloring all vertices with
+        $2$.
+    \item If your run into an already colored vertex, pick an arbitrary
+        uncolored vertex in this copy of $Q$ to color with $2$ and continue from
+        here.
+    \item Repeat steps 3.-5. for each successive color up to $|Q|$.
+\end{enumerate}
+
+Additionally, in each vertex, we store the index of the next copy of $Q$ in
+which the path of this vertex's color is broken by a lower color.
+
+\section{Least Common Ancestor via Range Minimum Query}
+
+\section{Highest Black Descendant on Path}
+
+We can now reduce the problem to the following:
+
+\emph{Given}: a tree $T$ with distinguished black vertices.
+
+\emph{Queries}: given a vertex $x$, its descendant $y$, find the node $z$ that
+is the highest black node on the path between $x$ and $y$.
+
+We will build an index structure, constructible in linear time, that allows us
+to handle such queries in constant time. The structure is heavily inspired by
+Schieber and Vishkin's structure for computing LCA queries. We will present our
+version of the structue in full detail, using Schieber and Vishkin's notation
+where possible.
+
+\subsection{High level overview}
+
+The LCA algorithm given by Schieber and Vishkin bases on two observations, first
+made by Harel and Tarjan:
+
+\begin{itemize}
+    \item LCA queries can be computed in constant time on \emph{simple paths}.
+    \item LCA queries can be computed in constant time on \emph{full binary trees}.
+\end{itemize}
+
+We map vertices of our tree $T$ to vertices of a full binary tree $B$ of size
+$O(n)$ that has two properties:
+
+\begin{enumerate}
+    \item The induced subgraph of all vertices mapped to the same node of $B$ is
+        a simple path in $T$.
+    \item If a vertex $v$ of $T$ is mapped to a vertex $b$ of $B$, all of its
+        descendants are mapped to descendants of $b$ (where $b$ is also a
+        descendant of itself).
+\end{enumerate}
+
+From 2. we get that also all of $v$'s ancestors are mapped to $b$'s ancestors in
+$B$, in particular they are all mapped into at most $\log(n)$ nodes of $B$.
+
+\section{Generalizing words to trees}
+
+\chapter{Conclusions}
+
+\end{document}
+
+%%% Local Variables:
+%%% mode: latex
+%%% TeX-master: t
+%%% coding: latin-2
+%%% End:
-- 
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