DocumentCode :
1363565
Title :
Reliability estimation from appropriate testing of plant protection software
Author :
May, J. ; Hughes, G. ; Lunn, A.D.
Author_Institution :
Dept. of Comput., Open Univ., Milton Keynes, UK
Volume :
10
Issue :
6
fYear :
1995
fDate :
11/1/1995 12:00:00 AM
Firstpage :
206
Lastpage :
218
Abstract :
Plant protection software may be realistically tested using inputs from a plant model before its initial use, or when it is not feasible to take the plant into certain fault conditions. If statistical estimation of software reliability is to be performed using the test results, it is not sufficient for the plant model to produce inputs which are simply correct in the sense that the plant could have produced them. In addition, the operational distribution of the input space must be simulated. This paper illustrates how to perform such a simulation, by developing an example in which an existing non-random plant model is randomised to simulate the operational distribution of the software. In addition, two methods of estimating the probability of failure on demand (PFD) for a program are reported. Both methods estimate a pfd given results from dynamic testing, during which the program is exercised according to its operational distribution. The first method is standard and has been used previously in the context of software testing. The second estimation method has been developed recently within a program of Nuclear Electric for research into software reliability testing. The distinguishing foundational assumptions of the two methods are discussed
Keywords :
fission reactor operation; fission reactor safety; nuclear engineering computing; nuclear power stations; power engineering computing; power plants; program testing; protection; software reliability; Nuclear Electric; dynamic testing; fault conditions; nonrandom plant model; nuclear power plant protection software; operational distribution; plant model inputs; probability of failure on demand; software reliability estimation; software reliability testing; software testing; statistical estimation;
fLanguage :
English
Journal_Title :
Software Engineering Journal
Publisher :
iet
ISSN :
0268-6961
Type :
jour
Filename :
668130
Link To Document :
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