diff --git a/chapter03.tex b/chapter03.tex
index 21349d4..441ea1d 100644
--- a/chapter03.tex
+++ b/chapter03.tex
@@ -326,7 +326,7 @@ of the algorithm is at least $O(n^2)$.
 It is possible to sort an array efficiently
 in $O(n \log n)$ time using algorithms
 that are not limited to swapping consecutive elements.
-One such algorithm is \key{mergesort}\footnote{According to \cite{knu98},
+One such algorithm is \key{mergesort}\footnote{According to \cite{knu983},
 mergesort was invented by J. von Neumann in 1945.}
 that is based on recursion.
 
diff --git a/chapter16.tex b/chapter16.tex
index f5e312d..09d99cb 100644
--- a/chapter16.tex
+++ b/chapter16.tex
@@ -657,7 +657,9 @@ achieves these properties.
 
 \index{Floyd's algorithm}
 
-\key{Floyd's algorithm} walks forward 
+\key{Floyd's algorithm}\footnote{The idea of the algorithm is mentioned in \cite{knu982}
+and attributed to R. W. Floyd; however, it is not known if Floyd was the first
+who discovered the algorithm.} walks forward 
 in the graph using two pointers $a$ and $b$.
 Both pointers begin at a node $x$ that
 is the starting node of the graph.
diff --git a/chapter17.tex b/chapter17.tex
index ba99272..b52dad6 100644
--- a/chapter17.tex
+++ b/chapter17.tex
@@ -368,7 +368,10 @@ performs two depth-first searches.
 \index{2SAT problem}
 
 Strongly connectivity is also linked with the
-\key{2SAT problem} \cite{asp79}.
+\key{2SAT problem}\footnote{The algorithm presented here was
+introduced in \cite{asp79}.
+There is also another well-known linear-time algorithm \cite{eve75}
+that is based on backtracking.}.
 In this problem, we are given a logical formula
 \[
 (a_1 \lor b_1) \land (a_2 \lor b_2) \land \cdots \land (a_m \lor b_m),
diff --git a/chapter18.tex b/chapter18.tex
index 2be2193..81c7ab3 100644
--- a/chapter18.tex
+++ b/chapter18.tex
@@ -676,7 +676,9 @@ nodes in $O(\log n)$ time using this technique.
 \subsubsection{Method 2}
 
 Another way to solve the problem is based on
-a tree traversal array \cite{ben00}.
+a tree traversal array\footnote{This lowest common ancestor algorithm is based on \cite{ben00}.
+This technique is sometimes called the \index{Euler tour technique}
+\key{Euler tour technique} \cite{tar84}.}.
 Once again, the idea is to traverse the nodes
 using a depth-first search:
 
@@ -719,8 +721,7 @@ However, we use a bit different tree
 traversal array than before:
 we add each node to the array \emph{always}
 when the depth-first search walks through the node,
-and not only at the first visit\footnote{A similar technique is sometimes called the
-\key{Euler tour technique} \cite{tar84}.}.
+and not only at the first visit.
 Hence, a node that has $k$ children appears $k+1$ times
 in the array and there are a total of $2n-1$
 nodes in the array.
diff --git a/list.tex b/list.tex
index 4bee692..d55e6b4 100644
--- a/list.tex
+++ b/list.tex
@@ -54,6 +54,11 @@
   Theoretical improvements in algorithmic efficiency for network flow problems.
   \emph{Journal of the ACM}, 19(2):248--264, 1972.
 
+\bibitem{eve75}
+  S. Even, A. Itai and A. Shamir.
+  On the complexity of time table and multi-commodity flow problems.
+  \emph{16th Annual Symposium on Foundations of Computer Science}, 184--193, 1975.
+
 \bibitem{fan94}
   D. Fanding.
   A faster algorithm for shortest-path -- SPFA.
@@ -141,7 +146,11 @@
   The statistics of dimers on a lattice: I. The number of dimer arrangements on a quadratic lattice.
   \emph{Physica}, 27(12):1209--1225, 1961.
 
-\bibitem{knu98}
+\bibitem{knu982}
+  D. E. Knuth.
+  \emph{The Art of Computer Programming. Volume 2: Seminumerical Algorithms}, Addison–Wesley, 1998 (3rd edition).
+
+\bibitem{knu983}
   D. E. Knuth.
   \emph{The Art of Computer Programming. Volume 3: Sorting and Searching}, Addison–Wesley, 1998 (2nd edition).