Analysis of Random Processes via And-Or Tree Evaluation
We introduce a new set of probabilistic analysis tools based on the analysis of And-Or trees with random inputs. These tools provide a unifying, intuitive, and powerful framework for carrying out the analysis of several previously studied random processes of interest, including random loss-resilient codes, solving random $k$-SAT formula using the pure literal rule, and the greedy algorithm for matchings in random graphs. In addition, these tools allow generalizations of these problems not previously analyzed to be analyzed in a straightforward manner. We illustrate our methodology on the three problems listed above.
Originally appeared in the Proceedings of the 9th Annual ACM Symposium on Discrete Algorithms, pp. 364--373, 1998.