  Software testing involves identifying the test cases whichdiscover errors in
the program. However, exhaustive testing ofsoftware is very time consuming. In
this paper, a technique isproposed to prioritize test case scenarios by
identifying the critical path clusters using genetic algorithm. The test case
scenarios are derived from the UML activity diagram and state chart diagram.
The testing efficiency is optimized by applying the genetic algorithm on the
test data. The information flow metric is adopted in this work for calculating
the information flow complexity associated with each node of the activity
diagram and state chart diagram.
