Premium
Importance measures for modular software with uncertain parameters
Author(s) -
Fiondella Lance N.,
Gokhale Swapna S.
Publication year - 2010
Publication title -
software testing, verification and reliability
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.216
H-Index - 49
eISSN - 1099-1689
pISSN - 0960-0833
DOI - 10.1002/stvr.420
Subject(s) - computer science , parametric statistics , modular design , context (archaeology) , reliability (semiconductor) , software , reliability engineering , risk analysis (engineering) , operations research , engineering , statistics , mathematics , medicine , paleontology , power (physics) , programming language , physics , quantum mechanics , biology , operating system
Importance measures provide a sense of the relative priorities of components and can be used to guide the allocation of resources for cost‐effective improvement of system reliability starting from the early phases. Uncertainties in model parameters, prevalent in the early phases, can introduce errors into these measures, and hence, importance assessment must account for these parametric uncertainties. In this paper, a framework for importance assessment of a software system within the context of its architecture is proposed. The framework includes two methods; the first one systematically quantifies the confidence intervals in the model parameters, and the second one offers an analytical approach for importance analysis. The two methods in conjunction address the issue of importance assessment in the face of parametric uncertainties. Illustration of the framework using a banking application demonstrates the value and benefits of the methodology. Copyright © 2009 John Wiley & Sons, Ltd.