(Supplement of Page 5)
Four techniques for finding lower bounds.
(1) Comparison tree.
(2) A particular problem instance.
(3) State transition.
(4) Problem reduction.
(Supplement of Page 7)
The progress of any comparison-based searching algorithm can be described by a path in a binary comparison tree.
Each internal node of the tree represents a comparison between x and some A[i].
Since the tree contains at least n internal nodes,
which represent the n possible successful occurrences of x in A, the tree depth is Ω(logn).
⇒ Comparison-based searching has a lower bound of Ω(logn).
(Supplement of Page 19)
For example, n=5.
There are five node-disjoint paths from 00000 to 01111 whose maximal length is n+1=6.
(00000, 01000, 01100, 01110, 01111) (00000, 00100, 00110, 00111, 01111) (00000, 00010, 00011, 01011, 01111) (00000, 00001, 01001, 01101, 01111)
(00000, 10000, 11000, 11100, 11110, 11111, 01111)