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A non‐parametric approach to software reliability
Author(s) -
Gandy Axel,
Jensen Uwe
Publication year - 2004
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.510
Subject(s) - covariate , computer science , multivariate statistics , software quality , parametric statistics , source code , reliability (semiconductor) , software , set (abstract data type) , code (set theory) , process (computing) , reliability engineering , data mining , statistics , software development , machine learning , programming language , engineering , mathematics , power (physics) , physics , quantum mechanics
In this paper we present a new, non‐parametric approach to software reliability. It is based on a multivariate counting process with additive intensity, incorporating covariates and including several projects in one model. Furthermore, we present ways to obtain failure data from the development of open source software. We analyse a data set from this source and consider several choices of covariates. We are able to observe a different impact of recently added and older source code onto the failure intensity. Copyright © 2004 John Wiley & Sons, Ltd.