Software Reliability Model Metrics: Precision and Robustness
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International Journal of Advanced Computer Science, Vol. 1, No. 6, Pp. 250-256, Dec. 2011. Manuscript Received: 5, Sep., 2011 Revised: 14,Nov., 2011 Accepted: 15,Dec., 2011 Published:15,Jan., 2012 Keywordssoftware reliability model, model precision, model robustness, classification AbstractSoftware reliability is the key factor among the characteristics software quality, and it is also the important index that hard to control and measure. On the basis of introducing the mechanism of software reliability models, this paper summarizes the present situation of the shortage of the generalization of the model. And it introduces two kinds of software reliability metrics. With the classification of software reliability of software life cycle, it will provide a useful criterion for the effective selection of software reliability. At last, it presents the conclusion and introduces the future work. 1.Introduction Almost all technologies which penetrate and control our modern life rely heavily on computer and computer software. However, today, none of the existing software products is fault-free. So ftware error s have known to cause spectacular and sometimes catastrophic failures. For example, on September 17, 1991, a power outage at the AT&T switching facility in New York City interrupted service to 10 million telephone customers for nine hours. During the 1991 Gulf War, a software problem may have prevented the Patriot missile system from tracking the Iraqi Scud missile the killed 28 U.S. soldiers. Giver the potential costly impact and possibly disastrous consequence of software failures for many applications, it is imperative to have sound methodologies to measure, quantify and improve software quality. This leads to the fact that software reliability is now an important research area. Software reliability is defined as the probability that the software will be functioning without failure under given environmental condition during a specific period of time [1]. Here, a software failure generally means the inability of This work was supported by National High Technology Research and Development Program of China (No: 2009AA01Z402). Z.W. Hui is with the department of Military Training Software Testing and Evaluation Centre, University of Science and Technology of PLA, Nanjing 2100 07, China. E-mail: hz w-1983821@163.com. X.M. Liu and S. Huang are with the Military Training Software Testing and Evaluation Centre of PLA, and Institute of Command Automation, PLA University of Science and Technology, Nanjing 210007, China. E-mail:nj-xml@16 3.com. hs-0317@s ohu.com. the software to perform an intended task specified by the requirement. As the complexity and size of software applications grow, number of faults in software design increases, hard to find and more subtle to detect. In recent years, the costs of developing software and fixing its inherent faults are major expenses in a system. Hence, reliability estimation and improvements techniques have proven to be useful tools for software developers to bring down cost, to evaluate current reliability, and to predict the future performance before releasing software products into market. In order to assess and enhance performance of the software, it is important to assess the reliability of the software for making important business decisions such as release of the software. Reliability models are a powerful tool for predicting, controlling, and assessing software reliability. The work on software reliability models started in 70’s, the first model being presented in 1972. Today the number of existing models exceeds hundred with more models developed every year. Still there does not exist any model that can be applied in all cases. Models that are good in general are not always the best choice for a particular data set, and it is not possible to know in advance what model should be used in any particular case [2]. There is not a guideline with high confidence level, which we can follow to choose any particular model. No one has succeeded in identifying a priori the characteristics of software that will ensure that a particular model can be trusted for reliability predictions [3]. This paper is organized as follows: section 2 presents mechanism and deficiency of traditional software. We first introduce the mechanism of deterministic models, and then gives the mechanism of probabilistic models. Section 3 exposes the measurement of software reliability models based on applicability analysis, and shows two metrics for software reliability models. In section 4, we briefly present a kind of classification of reliability models based on precision and robustness. Section 5 provides validation of the work. Finally, section 6 presents the conclusion and introduces the future work. Software Reliability Model Metrics: Precision and Robustness Zhanwei Hui, Xiaoming Liu, & Song Huang
