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Reliability verification test method based on mixed Bayesian prior distribution

A priori distribution and verification test technology, applied in software testing/debugging, etc., to achieve accurate prior distribution, reduce test load, and good fitting effect

Inactive Publication Date: 2012-04-11
HARBIN ENG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

But for other prior data, the hyperparameter calculation based on the conjugate maximum entropy method is not necessarily better than the calculation method based on prior moments

Method used

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  • Reliability verification test method based on mixed Bayesian prior distribution
  • Reliability verification test method based on mixed Bayesian prior distribution
  • Reliability verification test method based on mixed Bayesian prior distribution

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Embodiment

[0092] In the following embodiments of the present invention, the verification of the method of the present invention is realized in combination with MATLAB program simulation.

[0093] 20 random numbers are generated by beta(1, 22) through the MATLAB simulation program, which are:

[0094] x1=0.0587, x2=0.0027, x3=0.0774, x4=0.0958, x5=0.0134, x6=0.0635, x7=0.0921, x8=0.0016, x9=0.0036, x10=0.0552, x11=0.0221, x12=0.0539, x13= 0.0614, x14=0.0448, x15=0.0882, x16=0.0681, x17=0.0852, x18=0.0051, x19=0.0293, x20=0.0249.

[0095] Assume that the 20 groups of failure probability values ​​obtained by a software in a certain reliability test are X=(x1, x2, x3, x4, x5, x6, x7, x8, x9, x10, x11, x12, x13, x14, x15 , x16, x17, x18, x19, x20).

[0096] Based on the above prior information, use the prior moment method to calculate a according to the formulas (2.4) and (2.5) 1 =0.8,b 1 =24.1 utilize maximum entropy method to solve equation system (3.4) to draw a 2 =1.2,b 2 =23.3, and ...

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Abstract

The invention discloses a reliability verification test method based on mixed Bayesian prior distribution. According to the method, the prior distribution of unknown parameters is determined by adopting a conjugate prior distribution method; two different sets of parameters are obtained through a prior moment method and a maximal entropy method, namely different prior distributions are obtained; the weight of the two prior distributions is determined according to the second type of maximum likelihood method, parameters obtained through the prior moment method and the maximal entropy method are fused according to the weights, further, the prior distribution obtained finally is more accurate than prior distribution obtained through the separate adoption of anyone of the prior moment method and the maximal entropy method and better fits to the real distribution. In the method, the minimum number of zero-failure use cases required in the reliability verification test is calculated according to the Bayesian prior distribution and test information; therefore, compared with a method not based on prior knowledge, the method can be used for effectively reducing the quantity of use cases used in the test.

Description

technical field [0001] The invention relates to the field of software testing, in particular to a reliability verification testing method based on mixed Bayesian prior distribution. Background technique [0002] With the increasing application of computers in civilian and military products, product failures and catastrophic accidents caused by software defects are becoming more and more serious. Software reliability is an important guarantee for the reliability of the entire system, even a decisive factor. Software reliability testing is a very important step in the process of software reliability assurance. Reliability-tested software does not ensure that the software has a minimum number of remaining bugs, but it does ensure that the software meets high reliability requirements. From an engineering point of view, the high reliability of software means that the failure rate of the software is low, and it also means that once the software fails, the resulting damage is als...

Claims

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Application Information

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IPC IPC(8): G06F11/36
Inventor 高峰郑晓云李一晨李刚张振兴
Owner HARBIN ENG UNIV
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