Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6885350 | Journal of Systems and Software | 2018 | 30 Pages |
Abstract
To address the computational inefficiency of existing approaches, we employ Polynomial Chaos Expansion (PCE) as a rigorous method for uncertainty propagation and further extend its use to robust performance estimation. The aim is to assess if the software system is robust, i.e., it can withstand possible changes in parameter values, and continue to meet performance requirements. PCE is a very efficient technique, and requires significantly less computations to accurately estimate the distribution of performance indices. Through three very different case studies from different phases of software development and heterogeneous application domains, we show that PCE can accurately (â¯>â¯97%) estimate the robustness of various performance indices, and saves up to 225 h of performance evaluation time when compared to Monte Carlo Simulation.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Aldeida Aleti, Catia Trubiani, André van Hoorn, Pooyan Jamshidi,