The software reliability growth models (such as NHPP models) are frequently used in software reliability prediction. Estimation of parameters in these models is often done by point estimation. However, some numerical problems arise and make the actual computation hard, especially for automated reliability prediction tools. Here confidence interval computation in Goel-Okumoto model and S-shaped ...

Telecommunication networks, oil platforms, chemical plants and airplanes consist of a great number of subsystems and components that are all subject to failure. Reliability theory studies the failure behavior of such systems in relation to the failure behavior of their components, which is often easier to analyze. However, even for the most basic reliability models, the overall reliability of t...

software quality attribute and Software reliability estimation is a hard problem to solve accurately. However for management of software quality and standard practice of the organization, accurate reliability estimation is important. Non-homogeneous Poisson Process (NHPP) models and Artificial Neural Network (ANN) models are among the most important software reliability growth models. In this p...

System reliability is an important aspect of real-time systems, because the result of a real-time application may be valid only if the application functions correctly and its timing constraints are satisfied. There are two kinds of faults, hardware and software faults, and the paper considers hardware transient faults. Full replication or full hardware redundancy can achieve a high degree of re...

Software reliability models (SRMs) are very important for estimating and predicting software reliability in the testing/debugging phase. The contributions of this paper are as follows. First, a historical review of the Gompertz SRM is given. Based on several software failure data, the parameters of the Gompertz software reliability model are estimated using two estimation methods, the tradition...

In this paper, a new method to estimate the parameter for turbo decoding using the maximum a posteriori probability (MAP) algorithm is proposed for a turbo code in a Rayleigh fading channel with imperfect channel estimation. This parameter is called the channel reliability factor and is related with the channel SNR. For channel estimation, pilot symbol assisted modulation (PSAM) is used and the...

This paper proposes a reliability estimation method based on Step-Stress Accelerated Degradation Testing (SSADT) data analysis using unequal interval time series analysis. A MultiRegression Time Varying Auto-Regressive (MRTVAR) degradation time series model is proposed. Product SSADT data are treated as unequal interval composite time series and described using MRTVAR time series model and util...

Over 30 years of research have gone into software reliability engineering during testing. With today's complex software systems however, reliability has to be built into the early phases of development, including architectural design. We present a software architecture-based approach to estimating component reliability. Our sto-chastic reliability model is applicable to early stages of developm...

Aimed at the reparable characteristic of the mechanical product, a method of the reliability model recognition of mean time between failures based on the BP neural network was developed, and a method of parameter estimation of reliability model based on adaptive linear network was proposed by means of theory of artificial neural network with MATLAB and reliability engineering theory. By network...

Assessment of the reliability of various types of equipment relies on statistical inference about characteristics of reliability such as reliability function, mean lifetime of the devices, or failure rate. General techniques of statistical inference (estimation and hypotheses testing) are reviewed in Estimation; Least-Squares Estimation; Maximum Likelihood; Nonparametric Tests; Hypothesis Testi...