The proliferation of the wireless network over the last decade is one of the significant drivers for the increased deployment of mobile ad hoc networks (MANETs) in the battle field. It is not practically possible to build a fixed wired network infrastructure in battle field. But it is possible to create a mobile wireless network infrastructure because of the mobility of the soldiers. MANET is justified by the possibility of building a network where no infrastructure exists. MANET with group communication applications and multicasting can highly benefit from a networking environment such as military and emergency uses. In such applications, the used ad hoc networks need to be reliable and secure. In recent years, a specific technique called the universal generating function technique (UGFT) has been applied to determine the network reliability. The UGFT is based on an approach that is closely connected to generating functions that are widely used in probability theory. This work devotes to assess the MANET reliability using the UGFT. Reliability of the MANET is defined as the probability that the transformed message from the source can be passed successfully through the MANET and reached the target without any delay. Two kinds of UGFs are discussed in this work, and an algorithm has been proposed to execute the system reliability. This UGFT is illustrated with a case study in a battlefield environment. An MC consists of transmitting a packet to a group of mobile nodes identified by a single destination MC address and hence is intended for a group-oriented computing. The multicast service is employed in areas of a collaborative work, for example, in rescue operations, battlefields, video conferencing, and so on. An MC packet is typically delivered to all members of its destination group with the same reliability as regular unicast packets. An MC can reduce communication costs and the delivery delay. In addition, it can provide a robust communication mechanism when the receiver's individual address is changeable.Network reliability is an important part of planning, designing, and controlling network. There are many approaches for executing network reliability. 1-3 Chaturvedi and Misra 4 have proposed a hybrid method to evaluate the reliability of complex networks. Ahmad and Omid 5 have calculated the all terminal network reliability using recursive truncation algorithm. Some authors 6-9 have evaluated

Purpose -The purpose of this paper is to use Bayesian probability theory to analyze the software reliability model with multiple types of faults. The probability that all faults are detected and corrected after a series of independent software tests and correction cycles is presented. This in turn has a number of applications, such as how long to test a software, estimating the cost of testing, etc. Design/methodology/approach -The use of Bayesian probabilistic models, when compared to traditional point forecast estimation models, provides tools for risk estimation and allows decision makers to combine historical data with subjective expert estimates. Probability evaluation is done both prior to and after observing the number of faults detected in each cycle. The conditions under which these two measures, the conditional and unconditional probabilities, are the same is also shown. Expressions are derived to evaluate the probability that, after a series of sequential independent reviews have been completed, no class of fault remains in the software system by assuming the prior distribution as Poisson and binomial. Findings -From results in Sections 4 and 5 it can be observed that the conditional and unconditional probabilities are the same if the prior probability distribution is Poisson and binomial. In these cases the confidence that all faults are deleted is not a function of the number of faults observed during the successive reviews but it is a function of the number of reviews, the detection probabilities and the mean of the prior distribution. This is a remarkable result because it gives a circumstance in which the statistical confidence from a Bayesian analysis is actually independent of all observed data. From the result in Section 4 it can be seen that exponential formula could be used to evaluate the probability that no fault remains when a Poisson prior distribution is combined with a multinomial detection process in each review cycle. Originality/value -The paper is part of research work for a PhD degree.

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The Jelinski-Moranda (JM) model for software failures was one of the first models used for analyzing software reliability. Later Moranda proposed a modification of the JM model, labeled Geometric de-Eutrophication model. In the Moranda Geometric de-Eutrophication model, N (t) is defined as the number of faults detected in the time interval (0, t]. In this paper, N (t) is assumed to be a pure stochastic birth process, where failure rates decrease geometrically with a detection and rectifying of a fault. In this paper, a recursive scheme is proposed for studying the probability of detecting n bugs in the time (0, t]. The method uses a constructed table, which makes the method easier compared to other existing methods for computing P n (t), the intensity function and the reliability R τ (t). In the proposed procedure P n (t) is the sum of (n + 1) terms and each term is based on a factor, which can be from the above mentioned table. c c c c 6

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