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Software reliability model parameter estimation method based on genetic algorithm

A genetic algorithm and model parameter technology, applied in the field of software reliability modeling, to achieve the effect of improving computing speed, good local optimization ability, and accurate prediction ability

Pending Publication Date: 2021-11-02
CASIC DEFENSE TECH RES & TEST CENT
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Problems solved by technology

[0003] In the past 40 years, a large number of time-dependent NHPP (non-homogeneous Poisson process, non-homogeneous Poisson process) software reliability growth models have been proposed to evaluate the reliability of software systems, and most failures obey linear introduced, in many cases with certain limitations
Moreover, the software reliability growth model has many parameters, and the quality of the parameters has a great influence on the prediction accuracy of the model. At present, the commonly used methods are the maximum likelihood estimation or the least squares estimation algorithm, but these methods have certain limitations. , the partial derivative of the model function is required to exist and be continuous. If the model is nonlinear or has many parameters, it is difficult for conventional methods to solve such problems

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  • Software reliability model parameter estimation method based on genetic algorithm
  • Software reliability model parameter estimation method based on genetic algorithm
  • Software reliability model parameter estimation method based on genetic algorithm

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[0027] In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0028] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure shall have ordinary meanings understood by those skilled in the art to which the present disclosure belongs. The words "comprising" or "comprising" and other similar words used in the embodiments of the present disclosure mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects . "First," "second," and similar terms do not denote any order, quantity, or importance, but are used only to distinguish various components.

[0029] As mentioned in the backgr...

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Abstract

The invention provides a software reliability model parameter estimation method based on a genetic algorithm. The method comprises the following steps: acquiring a nonlinear function of a software reliability model; generating a population for the non-linear function; calculating the fitness value of each individual in the population according to the selected fitness function; based on the fitness value, selecting individuals entering the next generation from the population by using a roulette algorithm; performing crossover operation and gene mutation on the selected individuals to obtain offspring individuals; and replacing all individuals in the population with the offspring individuals, and carrying out iteration until a search result meeting a predetermined requirement is obtained. Parameter estimation of the software reliability model is accurately and effectively realized by utilizing optimization algorithms such as a genetic algorithm, and the method has good local optimization capability and is not limited by existence and continuity of a model function derivative.

Description

technical field [0001] The present disclosure relates to software reliability modeling, in particular to a method for estimating parameters of a software reliability model based on a genetic algorithm. Background technique [0002] Software plays an important role in many critical applications such as air traffic control systems, national security defense systems, embedded systems, etc. The functionality and correctness of software have received great attention. Software reliability has become the most important aspect of software quality. It is very important to quantitatively evaluate software reliability through effective methods. [0003] In the past 40 years, a large number of time-dependent NHPP (non-homogeneous Poisson process, non-homogeneous Poisson process) software reliability growth models have been proposed to evaluate the reliability of software systems, and most failures obey linear Introduced, in many cases has certain limitations. Moreover, the software re...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F8/77G06N3/12
CPCG06F8/77G06N3/126
Inventor 徐如远张生鹏王刚李晋鹏蒲泽良
Owner CASIC DEFENSE TECH RES & TEST CENT
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