ESTIMATING THE PROBABILITY OF FAILURE WHEN TESTING REVEALS NO FAILURES

被引：126
|
作者：
MILLER, KW
MORELL, LJ
NOONAN, RE
PARK, SK
NICOL, DM
MURRILL, BW
VOAS, JM
机构：
[1] COLL WILLIAM & MARY,DEPT COMP SCI,WILLIAMSBURG,VA 23185
[2] HAMPTON UNIV,COMP SCI,HAMPTON,VA 23368
[3] VIRGINIA COMMONWEALTH UNIV,DEPT MATH SCI,RICHMOND,VA 23284
[4] NASA,LANGLEY RES CTR,HAMPTON,VA 23665
来源：
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING | 1992年 / 18卷 / 01期
关键词：
BAYESIAN ESTIMATION; INPUT DISTRIBUTIONS; PROBABILITY OF FAILURE; REUSABLE SOFTWARE; SOFTWARE RELIABILITY; SOFTWARE TESTING;
D O I：
10.1109/32.120314
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
In this paper we introduce formulae for estimating the probability of failure when testing reveals no errors. These formulae incorporate random testing results, information about the input distribution, and prior assumptions about the probability of failure of the software. The formulae are not restricted to equally-likely input distributions, and the probability of failure estimate can be adjusted when assumptions about the input distribution change. The formulae are based on a discrete sample space statistical model of software and include Bayesian prior assumptions. Reusable software and software in life-critical applications are particularly appropriate candidates for this type of analysis.
引用
收藏
页码：33 / 43
页数：11
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