With the proliferation of multi-core systems in the last decade or so even the personal computers have acquired the capability of supporting parallel programs. However, most applications are simply not designed to take advantage of this capability. This is firstly due to the difficulty in comprehending parallel programs. Secondly, the speed-up achieved due to parallelism is diminished by the overhead incurred. We study both these aspects in the context of fork/join, the parallel programming framework supported by Java and Java Interactive Visualization Environment (JIVE), a dynamic analysis framework for debugging and visualizing Java programs. In this paper, we demonstrate how JIVE can be used to decode parallel program execution and their behavior on single, dual and quad core systems. We also present the results of the performance study undertaken to compare the performance of parallel programs against their sequential and multi-threaded counterparts for small, medium and large sized executions.