BugFixing in Distributed Environment using Multiple objective Partical Swarm Optmizat

[Academic_Project Reports]

BugFixing in Distributed Environment using Multiple objective Partical Swarm Optmization

All enterprise applications are now-a-days using highly complex software applications for its day-to-day activities. When a system is developed , it is thoroughly checked for bugs and then implemented so that there is a little possibility of the application to go wrong. But there is a great possibility of the system to incur problems when the requirements does not meet the system. When this happens this is also considered as bugs. If these bugs are found in the system the processing efficiency of the system decreases.
Asynchronous particle updates are shown to negatively impact the convergence speed in regards to iterations completed, however the increased parallel efficiency of the asynchronous model appears to counter this performance reduction, ensuring the asynchronous update mechanism performs comparably to the synchronous mechanism in fault-free environments. When faults are introduced, the synchronous update method is shown to suffer significant performance drops, suggesting that at least partly asynchronous algorithms should be used in real-world environments where faults can regularly occur.