Improve grammar and language style in chapter 3
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@ -9,12 +9,12 @@ use sorting as a subroutine,
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because it is often easier to process
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because it is often easier to process
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data if the elements are in a sorted order.
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data if the elements are in a sorted order.
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For example, the problem ''does the array contain
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For example, the problem ''does an array contain
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two equal elements?'' is easy to solve using sorting.
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two equal elements?'' is easy to solve using sorting.
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If the array contains two equal elements,
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If the array contains two equal elements,
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they will be next to each other after sorting,
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they will be next to each other after sorting,
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so it is easy to find them.
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so it is easy to find them.
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Also the problem ''what is the most frequent element
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Also, the problem ''what is the most frequent element
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in the array?'' can be solved similarly.
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in the array?'' can be solved similarly.
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There are many algorithms for sorting, and they are
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There are many algorithms for sorting, and they are
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@ -316,7 +316,7 @@ in the wrong order removes exactly one inversion
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from the array.
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from the array.
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Hence, if a sorting algorithm can only
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Hence, if a sorting algorithm can only
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swap consecutive elements, each swap removes
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swap consecutive elements, each swap removes
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at most one inversion and the time complexity
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at most one inversion, and the time complexity
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of the algorithm is at least $O(n^2)$.
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of the algorithm is at least $O(n^2)$.
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\subsubsection{$O(n \log n)$ algorithms}
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\subsubsection{$O(n \log n)$ algorithms}
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@ -327,10 +327,10 @@ It is possible to sort an array efficiently
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in $O(n \log n)$ time using algorithms
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in $O(n \log n)$ time using algorithms
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that are not limited to swapping consecutive elements.
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that are not limited to swapping consecutive elements.
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One such algorithm is \key{merge sort}\footnote{According to \cite{knu983},
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One such algorithm is \key{merge sort}\footnote{According to \cite{knu983},
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mergesort was invented by J. von Neumann in 1945.}
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merge sort was invented by J. von Neumann in 1945.},
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that is based on recursion.
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which is based on recursion.
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Mergesort sorts a subarray \texttt{t}$[a,b]$ as follows:
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Merge sort sorts the subarray \texttt{t}$[a,b]$ as follows:
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\begin{enumerate}
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\begin{enumerate}
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\item If $a=b$, do not do anything, because the subarray is already sorted.
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\item If $a=b$, do not do anything, because the subarray is already sorted.
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@ -519,8 +519,8 @@ ways to sort the array, a total of $n!$ ways.
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For this reason, the height of the tree
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For this reason, the height of the tree
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must be at least
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must be at least
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\[ \log_2(n!) = \log_2(1)+\log_2(2)+\cdots+\log_2(n).\]
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\[ \log_2(n!) = \log_2(1)+\log_2(2)+\cdots+\log_2(n).\]
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We get an lower bound for this sum
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We get a lower bound for this sum
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by choosing last $n/2$ elements and
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by choosing the last $n/2$ elements and
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changing the value of each element to $\log_2(n/2)$.
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changing the value of each element to $\log_2(n/2)$.
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This yields an estimate
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This yields an estimate
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\[ \log_2(n!) \ge (n/2) \cdot \log_2(n/2),\]
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\[ \log_2(n!) \ge (n/2) \cdot \log_2(n/2),\]
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@ -541,7 +541,7 @@ An example of such an algorithm is
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$O(n)$ time assuming that every element in the array
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$O(n)$ time assuming that every element in the array
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is an integer between $0 \ldots c$ and $c=O(n)$.
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is an integer between $0 \ldots c$ and $c=O(n)$.
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The algorithm creates a \emph{bookkeeping} array
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The algorithm creates a \emph{bookkeeping} array,
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whose indices are elements in the original array.
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whose indices are elements in the original array.
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The algorithm iterates through the original array
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The algorithm iterates through the original array
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and calculates how many times each element
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and calculates how many times each element
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@ -604,7 +604,7 @@ in the bookkeeping array is 2,
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because the element 3 appears 2 times
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because the element 3 appears 2 times
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in the original array (positions 2 and 6).
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in the original array (positions 2 and 6).
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The construction of the bookkeeping array
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Construction of the bookkeeping array
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takes $O(n)$ time. After this, the sorted array
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takes $O(n)$ time. After this, the sorted array
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can be created in $O(n)$ time because
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can be created in $O(n)$ time because
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the number of occurrences of each element can be retrieved
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the number of occurrences of each element can be retrieved
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@ -614,7 +614,7 @@ sort is $O(n)$.
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Counting sort is a very efficient algorithm
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Counting sort is a very efficient algorithm
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but it can only be used when the constant $c$
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but it can only be used when the constant $c$
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is so small that the array elements can
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is small enough, so that the array elements can
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be used as indices in the bookkeeping array.
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be used as indices in the bookkeeping array.
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\section{Sorting in C++}
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\section{Sorting in C++}
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@ -630,9 +630,9 @@ the function \texttt{sort} that can be easily used for
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sorting arrays and other data structures.
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sorting arrays and other data structures.
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There are many benefits in using a library function.
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There are many benefits in using a library function.
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First, it saves time because there is no need to
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Firstly, it saves time because there is no need to
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implement the function.
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implement the function.
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In addition, the library implementation is
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Secondly, the library implementation is
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certainly correct and efficient: it is not probable
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certainly correct and efficient: it is not probable
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that a self-made sorting function would be better.
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that a self-made sorting function would be better.
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@ -674,8 +674,8 @@ For example, the string ''monkey'' becomes ''ekmnoy''.
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The function \texttt{sort} requires that
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The function \texttt{sort} requires that
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a \key{comparison operator} is defined for the data type
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a \key{comparison operator} is defined for the data type
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of the elements to be sorted.
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of the elements to be sorted.
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During the sorting, this operator will be used
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When sorting, this operator will be used
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whenever it is needed to find out the order of two elements.
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whenever it is necessary to find out the order of two elements.
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Most C++ data types have a built-in comparison operator,
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Most C++ data types have a built-in comparison operator,
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and elements of those types can be sorted automatically.
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and elements of those types can be sorted automatically.
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@ -684,10 +684,10 @@ and strings are sorted in alphabetical order.
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\index{pair@\texttt{pair}}
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\index{pair@\texttt{pair}}
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Pairs (\texttt{pair}) are sorted primarily by their first
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Pairs (\texttt{pair}) are sorted primarily according to their
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elements (\texttt{first}).
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first elements (\texttt{first}).
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However, if the first elements of two pairs are equal,
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However, if the first elements of two pairs are equal,
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they are sorted by their second elements (\texttt{second}):
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they are sorted according to their second elements (\texttt{second}):
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\begin{lstlisting}
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\begin{lstlisting}
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vector<pair<int,int>> v;
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vector<pair<int,int>> v;
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v.push_back({1,5});
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v.push_back({1,5});
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@ -719,14 +719,14 @@ User-defined structs do not have a comparison
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operator automatically.
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operator automatically.
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The operator should be defined inside
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The operator should be defined inside
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the struct as a function
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the struct as a function
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\texttt{operator<}
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\texttt{operator<},
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whose parameter is another element of the same type.
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whose parameter is another element of the same type.
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The operator should return \texttt{true}
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The operator should return \texttt{true}
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if the element is smaller than the parameter,
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if the element is smaller than the parameter,
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and \texttt{false} otherwise.
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and \texttt{false} otherwise.
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For example, the following struct \texttt{P}
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For example, the following struct \texttt{P}
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contains the x and y coordinate of a point.
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contains the x and y coordinates of a point.
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The comparison operator is defined so that
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The comparison operator is defined so that
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the points are sorted primarily by the x coordinate
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the points are sorted primarily by the x coordinate
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and secondarily by the y coordinate.
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and secondarily by the y coordinate.
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