Last update: Sun Aug 5 02:03:07 MDT 2018
@Article{Zeil:2000:RGM,
author = "Steven J. Zeil",
title = "Reliability growth modeling from fault failure rates",
journal = j-SIGSOFT,
volume = "25",
number = "1",
pages = "94",
month = jan,
year = "2000",
CODEN = "SFENDP",
DOI = "https://doi.org/10.1145/340855.341045",
ISSN = "0163-5948 (print), 1943-5843 (electronic)",
ISSN-L = "0163-5948",
bibdate = "Wed Aug 1 17:13:50 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/sigsoft2000.bib",
abstract = "A variety of reliability growth models provide
quantified measures of test effectiveness in terms that
are directly relevant to project management [Lyu96],
but at the cost of restricting testing to
representative selection, in which test data is chosen
to reflect the operational distribution of the
program's inputs. During testing, data is collected on
the observed times between program failures (or,
similarly, numbers of failures within a time interval).
These observations are fitted to one of various models,
which can then be used to estimate the current
reliability of the program.",
acknowledgement = ack-nhfb,
fjournal = "ACM SIGSOFT Software Engineering Notes",
journal-URL = "https://dl.acm.org/citation.cfm?id=J728",
}