Title :
Performance prediction in early stages of software systems: Artificial neural network model
Author :
Ajitha, S. ; Kumar, T. V Suresh ; Geetha, D. Evangelin ; Rajnikanth, K.
Author_Institution :
M.S Ramaiah Inst. of Technol., Bangalore, India
Abstract :
Performance is an important non functional aspect to be considered for any software system. Software Performance Engineering (SPE) is an approach to predict the performance of a software system early in the life cycle. In this paper we present a neural network model for the performance prediction of Multi-Agent system at the early stages of development. We used Feed forward back propagation neural network model for the performance prediction. The results are validated and a case study of Multi-Agent System is presented.
Keywords :
backpropagation; feedforward neural nets; multi-agent systems; software performance evaluation; artificial neural network model; feed forward back propagation neural network model; multiagent system; performance prediction; software performance engineering; Artificial neural networks; Estimation; Software systems; Time factors; Training; Unified modeling language; Multi-Agent systems; Neural Network; Software performance engineering; UML models;
Conference_Titel :
Communication Control and Computing Technologies (ICCCCT), 2010 IEEE International Conference on
Conference_Location :
Ramanathapuram
Print_ISBN :
978-1-4244-7769-2
DOI :
10.1109/ICCCCT.2010.5670742
