In this author's opinion, following are the most important software quality attributes - Reliability, Usability, Performance and Availability. As said wisely, "Things that count most, can not be counted mostly." This paper tries to... more
In this author's opinion, following are the most important software quality attributes - Reliability, Usability, Performance and Availability. As said wisely, "Things that count most, can not be counted mostly." This paper tries to suggest how 'Reliability' can be measured from end user's perspective. For any software system, end user is the most important actor. Measuring ‘Reliability’ is a way to quantify the usefulness of the software for and end user. Therefore, measuring Reliability from an end user's perspective is very important. Unfortunately, there doesn't seem to be much discussion about how much reliable the software is for end user
In this paper using the main feature of our proposed Model in its inflection point, we propose a software reliability growth model, which relatively early in the testing and debugging phase, provides accurate parameters estimation, gives... more
In this paper using the main feature of our proposed Model in its inflection point, we propose a software reliability growth model, which relatively early in the testing and debugging phase, provides accurate parameters estimation, gives a very good failure behavior prediction and enable software developers to predict when to conclude testing, release the software and avoid over testing in order to cut the cost during the development and the maintenance of the software. Two real world experimental data previously analyzed have been used to compare our proposed Early Estimation Logistic Model effectiveness with several pre-existing models.
Analyzing the reliability of a software can be done at various phases during the development of engineering software. Software reliability growth models (SRGMs) assess, predict, and controlthe software reliability based on data obtained... more
Analyzing the reliability of a software can be done at various phases during the development of engineering software. Software reliability growth models (SRGMs) assess, predict, and controlthe software reliability based on data obtained from testing phase.This paper gives a literaturereview of the first and wellknownJelinski and Moranda(J-M) (1972)SRGM.Also a modification to Jelinski and Morandamodel is given, Jelinski and Moranda and Schick and Wolverton (S-W) (1978)SRGMsare two special cases of our new suggested general SRGM. Our proposed general SRGMalong with our Survey will open doors for much more useful researches to be done in the field of reliability modeling.
Number of software Reliability growth models has been proposed in the literature. A mathematical technique which describes the software testing phenomenon known as the software reliability growth model. Software reliability growth models... more
Number of software Reliability growth models has been proposed in the literature. A mathematical technique which describes the software testing phenomenon known as the software reliability growth model. Software reliability growth models are used to predict the number of faults and reliability of the software. In the view of this software reliability growth models are basically differentiated as the continuous and discrete models. There is a plenty of development in the continuous models but little towards the discrete models. In this paper we have presented a discrete reliability growth model with different discrete testing effort functions and the same time software release policy is discussed. A new imperfect debugging discrete software reliability growth model with testing effort is proposed. All calculations are done on real data. The results shows the proposed testing effort models are perfectly fit to the data.
The paper is based on Fuzzy Logic (FL) and Neural Network (NN) techniques to predict the software reliability using the MATLAB toolbox. There are four methods used in this paper to predict reliability of the dataset retrieved from John... more
The paper is based on Fuzzy Logic (FL) and Neural Network (NN) techniques to predict the software reliability using the MATLAB toolbox. There are four methods used in this paper to predict reliability of the dataset retrieved from John Musa of bell laboratories. These methods are fuzzy method, neural network, fuzzy-neural network and neural-fuzzy. After the assessment of data the results we achieved were best from the fuzzy-neural method among all proposed methods. In Fuzzy-neural method the Levenberg-Marquardt algorithm is used for training the neurons. The performance of our proposed approaches has been tested using the testing data, which 15% of the data from failure data set.
This paper is about studying the mixture of the Weibull−log−logistic distributions under Bayesian perspective. This model can be considered as new class of flexible models for heterogeneous lifetime data. Parameters of the model are... more
This paper is about studying the mixture of the Weibull−log−logistic distributions under Bayesian perspective. This model can be considered as new class of flexible models for heterogeneous lifetime data. Parameters of the model are estimated using the Gibbs sampling technique under type I censoring scheme. The behaviour of the Bayes estimators is studied assuming different priors. Finally, the model is applied to a real data set.
Abstract: Software reliability modeling is challenging since no single Software Reliability Growth Model (SRGM) is considered suitable in all situations owing to poor goodness of fit, lack of predictive validity of the models and their... more
Abstract: Software reliability modeling is challenging since no single Software
Reliability Growth Model (SRGM) is considered suitable in all situations owing to poor
goodness of fit, lack of predictive validity of the models and their sensitivity to
fluctuations in the number of failures in the data sets. In this paper, we propose a Non-
Homogenous Poisson Process Model whose failure intensity function has the same
Mathematical form as that of the probability density function (pdf) of a generalized
exponential distribution. The performance of the proposed model was verified and also
compared with six chosen SRGMs using failure data from 18 software systems and the
model is found to be adequate in terms of goodness
During the past few Decades, many software reliability growth models have been suggested for estimating reliability of software as software reliability growth models. The Functions suggested were non-linear in nature, so it was difficult... more
During the past few Decades, many software reliability growth models have been suggested for estimating reliability of software as software reliability growth models. The Functions suggested were non-linear in nature, so it was difficult to estimate the proper parameters. An Estimation method based on Ant Colony Algorithm in which parameters are estimated is discussed in this paper. In this paper, Numerical examples which have been based on five sets of real failure data have been discussed Using existing methods viable solutions for some of the models and data sets cannot be obtained, where as in the proposed method, at least one solution can be obtained. The accuracy of the results using proposed method when compared with PSO algorithm has higher accuracy for at least 10 times for majority of the models KEYWORDS Software Reliability Growth Model, Estimation, Particle Swam Optimization, Ant Colony Algorithm
Computer software has progressively turned out to be an essential component in modern technologies. Penalty costs resulting from software failures are often more considerable than software developing costs. Debugging decreases the error... more
Computer software has progressively turned out to be an essential component in modern technologies. Penalty costs resulting from software failures are often more considerable than software developing costs. Debugging decreases the error content but expands the software development costs. To improve the software quality, software reliability engineering plays an important role in many aspects throughout the software life cycle. In this paper, we incorporate both imperfect debugging and change-point problem into the software reliability growth model(SRGM) based on the well-known exponential distribution the parameter estimation is studied and the proposed model is compared with the some existing models in the literature and is find to be better.
Software systems have become integral part of everyday life and dependency on these makes the assessment of their reliability, a crucial task in software development. To facilitate the assessment of software reliability, effective tools... more
Software systems have become integral part of everyday life and dependency on these makes the assessment of their reliability, a crucial task in software development. To facilitate the assessment of software reliability, effective tools and mechanisms are required. Classical approaches such as hypothesis testing are significantly time consuming as the conclusion can only be drawn after collecting huge amounts of data. Statistical methods like Sequential Analysis can be applied to arrive at a decision quickly. We propose to implement Sequential Probability Ratio Test (SPRT) for Burr Type III model based on time domain data. For this, parameters are estimated using Maximum Likelihood Estimation to apply SPRT on real time software failure datasets borrowed from different software projects
Defining strategies on how to perform quality assurance (QA) and how to control such activities is a challenging task for organizations developing or maintaining software and software-intensive systems. Planning and adjusting QA... more
Defining strategies on how to perform quality assurance (QA) and how to control such activities is a challenging task for organizations developing or maintaining software and software-intensive systems. Planning and adjusting QA activities could benefit from accurate estimations of the expected defect content of relevant artifacts and the effectiveness of important quality assurance activities. Combining expert opinion with commonly available measurement data in a hybrid way promises to overcome the weaknesses of purely data-driven or purely expert-based estimation methods. This article presents a case study of the hybrid estimation method HyDEEP for estimating defect content and QA effectiveness in the telecommunication domain. The specific focus of this case study is the use of the method for gaining quantitative predictions. This aspect has not been empirically analyzed in previous work. Among other things, the results show that for defect content estimation, the method performs significantly better statistically than purely data-based methods, with a relative error of 0.3 on average (MMRE).
Reliability is one of the most relevant software quality attributes. The literature offers a variety of mathematical models - namely, software reliability growth models (SRGMs) - to estimate the reliability of a software product at a... more
Reliability is one of the most relevant software quality attributes. The literature offers a variety of mathematical models - namely, software reliability growth models (SRGMs) - to estimate the reliability of a software product at a given time, as well as to predict the reliability that will be achieved as testing activities progress. One of the typical assumptions of SRGMs is the immediate debugging of detected faults. In reality, the impact of the debugging process cannot be neglected at all. This paper reports the results of a real-world case-study in which we analyze the debugging process of a Customer Relationship Management (CRM) system, and study its impact on SRGM-based reliability estimation and prediction.
