The problem of interest as indicated is to develop a general purpose technique that is a combination of the structural approach, and an extension of the Finite Inductive Sequence (FI) technique. FI technology is pre-algebra, and deals with patterns for which an alphabet can be formulated.

The main contribution of this dissertation proposes a new paradigm, called the parentheses matching paradigm. It claims that this paradigm is well suited for designing efficient parallel algorithms for a broad class of nonnumeric problems. To demonstrate its applicability, we present three cost-optimal parallel algorithms for breadth-first traversal of general trees, sorting a special class of integers, and coloring an interval graph with the minimum number of colors.

There is a natural tendency for biological systems to change as their environments change. The fittest in the biological systems survive, adapt to their environment, and multiply while the weakest in the environment diminish. There have been attempts in computer science to model the processes of natural selection and survival which occur in biological systems in order to obtain more efficient and effective machine-learning algorithms. Genetic algorithms are the result of these attempts.