Random walk on a graph is a Markov chain whose state space is the vertex set of the graph,
and whose transition from a given vertex to an adjacent vertex along an edge is defined according to some probability distribution.
Random walks can describe the structure of graphs, groups and related objects,
and the structure of computer networks or electric networks.
When deterministic methods to analyze them are known to be difficult, it is quite useful to devise probabilistic algorithms of random walks on graphs which reflect combinatorial problems.
It is well known that random walks play a crucial role in the design of randomized algorithms (off or on-line).
We study hitting time and investigate how to test the efficiency of pseudorandom number generators using random walks.
