Fixed exercise 4 GA4
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2 changed files with 13 additions and 18 deletions
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GA4/ga4.pdf
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GA4/ga4.tex
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GA4/ga4.tex
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@ -5,6 +5,7 @@
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\usepackage{xcolor}
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\usepackage{xcolor}
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\usepackage{lmodern}
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\usepackage{lmodern}
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\usepackage{listings}
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\usepackage{listings}
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\usepackage{hyperref}
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\title{Graded Assignment 4 -- DSA}
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\title{Graded Assignment 4 -- DSA}
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\author{Claudio Maggioni}
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\author{Claudio Maggioni}
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@ -194,12 +195,14 @@ edge in the minimal spanning tree. The other parameters must be given as describ
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FUNCTION IS-MST-MINIMAL(T=(V,E), weight, v, w, c):
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FUNCTION IS-MST-MINIMAL(T=(V,E), weight, v, w, c):
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P[w] = NIL
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P[w] = NIL
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DEFINE-PARENT(T, P, Adj[w], w)
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DEFINE-PARENT(T, P, Adj[w], w)
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edge1_w = weight($\textit{edge}$ (v, P[v]))
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s = v
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s = v
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while P[s] $\neq$ w:
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while s $\neq$ w:
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edge_w = weight($\textit{edge}$ (s, P[s]))
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if edge_w > c:
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return FALSE
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s = P[s]
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s = P[s]
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edge2_w = weight($\textit{edge}$ (s, w))
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return c > edge1_w $\land$ c > edge2_w
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return TRUE
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FUNCTION DEFINE-PARENT(G=(V,E), P, S, v):
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FUNCTION DEFINE-PARENT(G=(V,E), P, S, v):
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for each vertex u $\in$ S:
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for each vertex u $\in$ S:
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@ -208,27 +211,19 @@ FUNCTION DEFINE-PARENT(G=(V,E), P, S, v):
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\end{lstlisting}
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\end{lstlisting}
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The algorithm works by walking the entire tree with \texttt{DEFINE-PARENT} in order to define a parent relation considering $w$ as
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The algorithm works by walking the entire tree with \texttt{DEFINE-PARENT} in order to define a parent relation considering $w$ as
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the root. Then, this relation is used to define the path between $v$ and $w$, and the weights of the
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the root. Then, this relation is used to define the path between $v$ and $w$, and the weights of every edge in the path from $v$ to
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first outgoing edge from $v$ and the final edge to $w$ are memorized in \texttt{edge1\_w} and \texttt{edge2\_w}.
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$w$ are memorized in \texttt{edge\_w} and compared and checked against the weight of $(v, w)$. If we find an edge in the path with
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The complexity of this step is $O(|V|)$ since the total number of edges in a tree is linearly dependent to the number
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weight bigger than $(v, w)$ we can then replace that edge with $(v, w)$, so we return \texttt{FLASE}\textit{ (sic)}
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\footnote{\url{https://medium.com/@DanielC7/dbf8773df767}} since we the old MST is not minimal anymore.
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The complexity of this is $O(|V|)$ since the total number of edges in a tree is linearly dependent to the number
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of vertices (i.e.: $|E_T| = |V| - 1$).
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of vertices (i.e.: $|E_T| = |V| - 1$).
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Note that if $v$ and $w$ are adjacent then these two values are the same, but this does not compromise the algorithm.
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Finally, we check if $(v, w)$ is the the edge with highest weight with respect to \textit{edge1} and \textit{edge2}. If this is the
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case, then replacing \textit{edge1} or \textit{edge2} with $(v, w)$ would not give a spanning tree with minimum total weight, and
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thus we return \texttt{FALSE}. Otherwise, the opposite is true and we return \texttt{TRUE}. Note that this step is constant, so the
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total complexity is $O(|V|)$.
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\subsection{Point 2}
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\subsection{Point 2}
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\begin{lstlisting}[caption=Solution for exercise 4 point 2, label={lst:ex4p1}]
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\begin{lstlisting}[caption=Solution for exercise 4 point 2, label={lst:ex4p1}]
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FUNCTION MAKE-MST-MINIMAL(T=(V,E), weight, v, w, c):
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FUNCTION MAKE-MST-MINIMAL(T=(V,E), weight, v, w, c):
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if not IS-MST-MINIMAL(T, weight, v, w, c):
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if not IS-MST-MINIMAL(T, weight, v, w, c):
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if edge1_w < edge2_w:
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$\textit{delete edge where IS-MST-MINIMAL stopped from T}$
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$\textit{delete edge1 from T}$
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else:
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$\textit{delete edge2 from T}$
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$\textit{add (v, w) to T}$
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$\textit{add (v, w) to T}$
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\end{lstlisting}
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\end{lstlisting}
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