Abstract: Wide applicability of concurrent programming
practices in developing various software applications leads to
different concurrency errors amongst which data race is the most
important. Java provides greatest support for concurrent
programming by introducing various concurrency packages. Aspect
oriented programming (AOP) is modern programming paradigm
facilitating the runtime interception of events of interest and can be
effectively used to handle the concurrency problems. AspectJ being
an aspect oriented extension to java facilitates the application of
concepts of AOP for data race detection. Volatile variables are
usually considered thread safe, but they can become the possible
candidates of data races if non-atomic operations are performed
concurrently upon them. Various data race detection algorithms have
been proposed in the past but this issue of volatility and atomicity is
still unaddressed. The aim of this research is to propose some
suggestions for incorporating certain conditions for data race
detection in java programs at the volatile fields by taking into account
support for atomicity in java concurrency packages and making use
of pointcuts. Two simple test programs will demonstrate the results
of research. The results are verified on two different Java
Development Kits (JDKs) for the purpose of comparison.
Abstract: Parallel programming models exist as an abstraction
of hardware and memory architectures. There are several parallel
programming models in commonly use; they are shared memory
model, thread model, message passing model, data parallel model,
hybrid model, Flynn-s models, embarrassingly parallel computations
model, pipelined computations model. These models are not specific
to a particular type of machine or memory architecture. This paper
expresses the model program for concurrent approach to data parallel
model through java programming.