ENHANCEMENT AND COMPARISON OF ANT COLONY OPTIMIZATION FOR SOFTWARE RELIABILITY MODELS

In Common parlance, the traditional software reliability estimation methods often rely on assumptions like statistical distributions that are often dubious and unrealistic. The ability to predict the number of faults during development phase and a proper testing process helps in specifying timely release of software and efficient management of project resources. In the Present Study Enhancement and Comparison of Ant Colony Optimization Methods for Software Reliability Models are studied and the estimation accuracy was calculated. The Enhanced method shows significant advantages in finding the goodness of fit for software reliability model such as finite and infinite failure Poisson model and binomial models

Програмне забезпечення SERC для аналізу похибки оцінки надійності відмовостійких реконфігуровних багатопроцесорних систем

Розглядаються питання розрахунку імовірності безвідмовної роботи відмовостійких реконфігуровних багатопроцесорних систем. Дається коротке описання розробленого програмного забезпечення SERC (Statistical Experiments for Reliability Calculation), в якому реалізовано відомі та запропоновані модифікації методу статистичних випробувань для розрахунку показників надійності ВБС та засоби для оцінки похибки розрахунку.Рассматриваются вопросы расчета вероятности безотказной работы отказоустойчивых реконфигурируемых многопроцессорных систем (ОМС). Дается краткое описание разработанного программного обеспечения SERC (Statistical Experiments for Reliability Calculation), в котором реализованы известные и предложенные автором модификации метода статистических испытаний для расчета надежности ОМС и средства для оценки погрешности расчета.The article devoted to reliability estimation of fault-tolerant reconfigurable multiprocessor systems. The paper briefly describes implementation of software SERC (Statistical Experiments for Reliability Calculation) which contains known and proposed by author statistical methods for fault tolerant reconfigurable multiprocessor systems reliability estimation and tools for Monte Carlo Error analysis of the estimation

Software Reliability Using SPRT: Burr Type III Process Model

Increased dependence on software systems elicited the assessment of their reliability, a crucial task in software development. Effective tools and mechanisms are required to facilitate the assessment of software reliability. Classical approaches like hypothesis testing are significantly time consuming as the conclusion can only be drawn after collecting huge amounts of data. Statistical method such as Sequential Analysis can be applied to arrive at a decision quickly. This paper implemented Sequential Probability Ratio Test (SPRT) for Burr Type III model based on time domain data. For this, parameters were estimated using Maximum Likelihood Estimation to apply SPRT on five real time software failure datasets borrowed from different software projects. The results exemplify that the adopted model has given a rejection decision for the used datasets

Monitoring Networked Applications With Incremental Quantile Estimation

Networked applications have software components that reside on different computers. Email, for example, has database, processing, and user interface components that can be distributed across a network and shared by users in different locations or work groups. End-to-end performance and reliability metrics describe the software quality experienced by these groups of users, taking into account all the software components in the pipeline. Each user produces only some of the data needed to understand the quality of the application for the group, so group performance metrics are obtained by combining summary statistics that each end computer periodically (and automatically) sends to a central server. The group quality metrics usually focus on medians and tail quantiles rather than on averages. Distributed quantile estimation is challenging, though, especially when passing large amounts of data around the network solely to compute quality metrics is undesirable. This paper describes an Incremental Quantile (IQ) estimation method that is designed for performance monitoring at arbitrary levels of network aggregation and time resolution when only a limited amount of data can be transferred. Applications to both real and simulated data are provided.Comment: This paper commented in: [arXiv:0708.0317], [arXiv:0708.0336], [arXiv:0708.0338]. Rejoinder in [arXiv:0708.0339]. Published at http://dx.doi.org/10.1214/088342306000000583 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Forecasting of Warranty Returns Based on the Reliability of Delivery Assessment

The paper presents a method to evaluate the reliability of deliveries with the application of Reliasoft Weibull++ software. The first stage in the proposed method was to collect data on outbound deliveries on a monthly basis and convert them into reliability data (life data). Next, by combining selected statistical tests and the maximum likelihood estimation method, the most accurate model of reliability of deliveries was obtained. Using the model which was generated, selected reliability indices were determined, such as: reliability of deliveries, unreliability of deliveries, failure rate of deliveries. Consequently, the number of future failed deliveries was forecast, taking into account the confidence bounds. The approach presented may be easily applied in companies in the logistics sector. The authors underlined that the reliability of deliveries is one of the key factors determining business competitiveness

A tutorial on Bayesian single-test reliability analysis with JASP

The current practice of reliability analysis is both uniform and troublesome: most reports consider only Cronbach’s α, and almost all reports focus exclusively on a point estimate, disregarding the impact of sampling error. In an attempt to improve the status quo we have implemented Bayesian estimation routines for five popular single-test reliability coefficients in the open-source statistical software program JASP. Using JASP, researchers can easily obtain Bayesian credible intervals to indicate a range of plausible values and thereby quantify the precision of the point estimate. In addition, researchers may use the posterior distribution of the reliability coefficients to address practically relevant questions such as “What is the probability that the reliability of my test is larger than a threshold value of .80?”. In this tutorial article, we outline how to conduct a Bayesian reliability analysis in JASP and correctly interpret the results. By making available a computationally complex procedure in an easy-to-use software package, we hope to motivate researchers to include uncertainty estimates whenever reporting the results of a single-test reliability analysis

Метод статистического оценивания и определения временных параметров моделей совмещения красок в печатных машинах

В статті досліджено метод статистичного оцінювання та визначення часових параметрів моделей суміщення фарб в паперопередавальній системі для забезпечення точності та достовірності контролю параметрів суміщення фарб у друкарських машинах.In the article the method of statistical estimation and timing parameters of models register the colors in sheet transfer system to ensure the accuracy and reliability of the control parameters of register the colors in printing press. The use of digital parameters determination register the colors allows the use of statistical estimation process measurement results by improving the reliability and accuracy of the amplitude-time parameters of pulse signals that model parameters diagonal, transversal and longitudinal register the colors. So important is the study of the method of statistical processing of amplitude parameters of pulse signals based on the criterion of Pearson and Shovene for reliable determination of the time parameters register the colors and models permits the use of problem-oriented software to automate the control register the colors in real time.В статье исследован метод статистического оценивания и определения временных параметров моделей совмещения красок в бумагопередающей системе для обеспечения точности и достоверности контроля параметров совмещения красок в печатных машинах

Estimating Reliability for Frechet (3+1) Cascade Model

In this paper, the mathematical formula of the reliability function of a special (3+1) cascade model is found, where this model can work with three active components if it is able to cope with the stresses to which it is subjected, while the cascade 3+1 model consists of four components, where the components (A1,A2 and A3) are the basic components in the model and component (A4)  is a spare component in an active state of readiness, so when any of the three core components (A1,A2 and A3)  fails to  copy with the stress they are under and stops working, they are replaced by the standby component  (A4) readiness to keep the model running, it was assumed that the random variables of stress and strength follow one of the statistical life distributions, which is the Frechet distribution. The unknown parameters of the Ferchet distribution were estimated by three different estimation methods (maximum likelihood, least square, and regression), and then the reliability function of the model was estimated by these different methods. A Monte Carlo simulation was performed using MATLAB software to compare the results of different estimation methods and find out which methods are the best for estimating the reliability of the model using two statistical criteria: MSE and MAPE and using different sample sizes. After completing the comparison of the simulation results, it was found that the maximum likelihood estimator is the best for estimating the reliability function of the model among the three different estimation method

Assessing Software Reliability Using Exponential Imperfect Debugging Model

Software reliability is one of the most important characteristics of software quality. As the usage of software reliability is growing rapidly, accessing the software reliability is a critical task in development of a software system. So, many Software Reliability Growth Models (SRGM) are used in order to decide upon the reliable or unreliable of the developed software very quickly. The well known software reliability growth model called as Exponential Imperfect Debugging model is a two parameter Non Homogeneous Poisson Process model which is widely used in software reliability growth modeling. In this paper, we propose to apply Statistical Process Control (SPC) to monitor software reliability process. A control mechanism is proposed based on the cumulative observations of failures which are grouped using mean value function of the Exponential Imperfect Debugging model. The Maximum Likelihood Estimation (MLE) approach is used to estimate the unknown parameters of the model. The process is illustrated by applying to real software failure data