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PurposeThe software development team reviews the testing phase to assess if the reliability growth of software is as per plan and requirement and gives suggestions for improvement. The objective of this study is to determine the optimal review time such that there is enough time to make judgments about changes required before the scheduled release.Design/methodology/approachTesting utilizes majority of time and resources, assures reliability and plays a critical role in release and warranty decision-making reviews necessary. A very early review during testing may not give useful information for analyzing or improving project performance, and a very late review may delay product delivery and lead to opportunity loss for developers. Therefore, it is assumed that the optimal time for review is in the later stage of testing when the fault removal rate starts to decline. The expression for this time point is determined using the S-curve 2-D software reliability growth model (SRGM).FindingsThe methodology has been illustrated using the real-life fault datasets of Tandem computers and radar systems resulting in optimal review time of 14 weeks and 26 months, respectively, which is neither very early in testing nor very near to the scheduled release. The developer can make changes (more resources or postpone release) to expedite the process.Originality/valueMost of the literature studies focus on determination of optimal testing or release time to achieve considerable reliability within the budget, but in this study, the authors determine the optimal review time during testing using SRGM to ensure the considerable reliability at release.

The open-source software (OSS) market comprises of thousands of products and applications with different quality. The primary concern of the individuals and organizations is to evaluate the quality OSS products and packages. In this chapter, we have demonstrated a MCDM based model to assess the quality of OSS by taking performance and cost-based criteria related with OSS to analyze its quality on the basis of feedback gathered from the users and the experts. To avoid the uncertainty attached with the opinion of the expert, the Maximum-Entropy-Minimum-Variance-Ordered-Weighted-Aggregation (MEMV-OWA) operator has been incorporated. The criteria weights are calculated by solving a non-linear multi-objective programming problem proposed in the MEMV-OWA operator. The picture fuzzy set information has been used which is an addendum of intuitionistic fuzzy set, representing the human opinion more precisely. In this chapter, we have proposed a model named MEMV-OWA-PF-TOPSIS (Maximum Entropy Minimum Variance-Ordered Weighted Aggregation-Picture-Fuzzy-TOPSIS). A step by step procedure has been exhibited to show its implementation in real-life problems. A numerical illustration related to the software quality assessment of OSS on the basis of their performance and cost-based criteria has also been provided in this study.

The planning and implementation of software development process should go hand in hand with the user expectations. It is crucial for firms to develop products catering user needs along with software engineers and programmers opinion. Many models have been developed in literature to allocate reliabilities to modules by setting system reliability goal based on hierarchy that inter-connects the attitudes of both developers and users. In this Chapter, we have proposed a hybrid reliability allocation model by integrating Analytical Hierarchical Process and reliability maximization problem for the software system based on the budget and reliability constraints. The comparison among functions, programs and modules by users, engineers and programmers respectively at different levels of hierarchy is performed under Neutrosophic environment to incorporate the vague and inconsistent information available. The relative weight obtained for each module is further used in optimization problem to finally allocate reliabilities to modules with the aim of maximizing the overall reliability of the software system considering the financial constraints associated with the project. The proposed methodology has been explained in detail and implemented through example problem.

Today’s software systems and applications are expanded in almost all the firms and are indulged in various business units that need customer base. The methodology of the multi-release software reliability growth model (SRGM) deals with customer demand and market requirements. There are various multi-release SRGMs given by researchers, but it is challenging to select the optimal model. Traditionally, a multi-criteria decision-making approach has been used to resolve the problem of the ranking of models. In this chapter, the Weighted Distance-based Approach has been proposed to rank the multi-release SRGMs using the Maximum Deviation Method (MDM) and Distance-Based approach (DBA). The models are ranked based on selection criteria having different priority weights and composite distance values. The method MDM is a technique of Multi Criteria Decision Making (MCDM) in which non-linear programming is performed.

PurposeThe purpose of this paper is to identify and quantify the key components of the overall cost of software development when warranty coverage is given by a developer. Also, the authors have studied the impact of imperfect debugging on the optimal release time, warranty policy and development cost which signifies that it is important for the developers to control the parameters that cause a sharp increase in cost.Design/methodology/approachAn optimization problem is formulated to minimize software development cost by considering imperfect fault removal process, faults generation at a constant rate and an environmental factor to differentiate the operational phase from the testing phase. Another optimization problem under perfect debugging conditions, i.e. without error generation is constructed for comparison. These optimization models are solved in MATLAB, and their solutions provide insights to the degree of impact of imperfect debugging on the optimal policies with respect to software release time and warranty time.FindingsA real-life fault data set of Radar System is used to study the impact of various cost factors via sensitivity analysis on release and warranty policy. If firms tend to provide warranty for a longer period of time, then they may have to bear losses due to increased debugging cost with more number of failures occurring during the warrantied time but if the warranty is not provided for sufficient time it may not act as sufficient hedge during field failures.Originality/valueEvery firm is fighting to remain in the competition and expand market share by offering the latest technology-based products, using innovative marketing strategies. Warranty is one such strategic tool to promote the product among masses and develop a sense of quality in the user’s mind. In this paper, the failures encountered during development and after software release are considered to model the failure process.

OSS development is remarkably different from paradigms of conventional software engineering. Although reliability modelling is an area of research since 1970s but reliability analysis for OSS is relatively recent. This paper tries to establish the reliability growth phenomenon for such software in terms of its usage in operational environment. This study further investigates the variation between number of faults detected and corrected as Fault Reduction Factor (FRF) and thus justifies its importance in reliability modelling under imperfect debugging. Three different trends of FRF are discussed in terms of number of users adopting the software with time. The proposed NHPP models for OSS are tested on two real-world fault datasets, namely, GNOME 2.0 and Firefox 3.0 and it is empirically deduced that the model precisely describes the failure process for OSS and thus can be adopted and further extended for reliability characterization.

Background: Snakebite is a major public health problem and its prevalence is high in India. Insufficient epidemiological data and global neglect of this condition prompted the World Health organization to recognize it as a ‘‘neglected tropical disease’’ Objective: To study demographic characteristics of snakebite victims, to see clinical symptoms of bite and outcomes of snakebite. Methods: A prospective observational hospital-based study carried out from November 2016 to October 2017, in patients with a history of snakebite. Results:Total 300 patients were included in this study,170 (56.67%) were bitten by heamotoxic snakes and 130 (43.33%) were bitten by neurotoxic snakes. Majority of patients were in the age group of 20-39 years ( n=153; 51%). Men outnumbered women( n=190; 63.33%), with male to female ratio of 1.7: 1. Higher incidence of snake bite was found in July – September (n=135;45.00 %) followed by April to June( n=124; 41.33%).Majority of patients were farmers in rural areas ( n=242; 80.80%).Out of 300 patients,80required ICU care.In patients with neuroparalytic snake bites, clinical features were; ptosis (n=126; 96.92%),ophthalmoplegia (n=98; 75.38%),respiratory paralysis (n=60; 46.15%),bulbar weakness ( n=74; 56.92%) andabdomen pain(n=25; 19.23%).Clinical features in patients of haemotoxic snake bites were ; bleeding from bite site(n=110; 65.29%) , cellulitis(n=100; 58.82%), gum bleed(n=53; 31.18%), ecchymosis(n=49; 28.82%),epistaxis(n=27; 15.82%),gastrointestinal bleeding(n=25; 14.71%) andhaemoptysis(n=19; 11.18%). Complications observed were acute kidney injury ( n=62; 20.67%) , respiratory failure ( n=51; 17.00%) , DIC( n=7; 2.33%) and ARDS( n=5; 1.67%) . Out of 170 hemotoxic snake bite patients, 157 (92.35%) patients recovered and 13 (7.65%) patients died and out of 130 neurotoxic snake bites, 124 (95.39%) patients recovered and 6 (4.61%) patients died, overall mortality was 6.3%. In our study, bite to needle time was less than 1 hour in 47 patients (15.66%), less than 6 hrs in 120 patients (40%) and more than 24 hours in 45 (15%). Conclusion: Snakebite is common in adult males between 20 to 50 years and the commonest site is the lower limb. The majority of the victims are farmers who work in fields. A maximum number of cases presented within 1-6 hours of bite using a tourniquet on the affected limb as first aid. The complications and mortality of snakebite are high.

Software development team intent to provide the best quality products under time and resource constraints. They single out their product in the market using various tools like advertisements, discounts, free trials, social networking etc. Warranty is one such tool used for product promotion. It assures customers from failure risks after product release. On one hand this helps to build the customer trust and brand image while on the other side it involves cost to developers in terms of cost incurred due to fault corrections during warranty period. Hence management has to maintain a balance so that they don’t have to bear undue financial losses. Therefore they plan release policies to determine the release time and the warranty time period that minimizes the cost. In this paper we have proposed a cost optimization model considering FRF based Two-Dimensional Delayed S-Shaped SRGM to define the failure behaviour under imperfect debugging, market opportunity cost, environmental factor and warranty policy. The model differentiates between the number of failures experienced and faults removed along with the probability of error generation. Once software is released it is affected by various external factors that may affect its failure behaviour. To accommodate the effect of external factor we have introduced an environment factor in the cost model. We have validated the model using the Tandem computers failure dataset. The optimization problem has been solved in MATLAB to determine optimal warranty and release time periods so that the total expected cost for software development is minimized.

Numerous Non-Homogenous Poisson Process based Software Reliability Growth Models have been developed in the past to assess reliability growth of the software system. In a contribution to existing literature, we study the impact of realistic factors encountered during the process of development. This paper proposes a reliability growth model incorporating Fault Reduction Factor, Fault Removal Efficiency and error generation to predict the reliability of the product released in multiple versions. Fault Reduction Factor has been modelled by Delayed S-shaped model, while Fault Removal Efficiency and Error Generation parameters are considered to be constant. Further, we validate the model on a four release real fault dataset of Tandem computers and employ data analysis techniques to plot goodness of fit curves and boxplots to investigate predictive accuracy of proposed model. We have also judged the experimental outcomes considering three special cases. It is witnessed that the proposed model well captures the failure phenomenon and the parameters considered significantly impacts the accuracy.

The bug is reported by different users of the software and gets fixed after it is verified and diagnosed. Once a bug is reported, it is triaged. The fix time of a bug is the time difference between bug resolved date and open date of the bug. The prior prediction of bug fix time will assist in resource management and in predicting the quality of the software product. The size of software repositories which consist of bugs, code, and archive communication is also increasing with enormous rate in the open-source environment. In this scenario, it is difficult to handle the large amount of datasets with the traditional approach. In this paper, we have used an extension called Radoop to enable the integration of RapidMiner with Hadoop to handle the big data of bug reports. We have used classification techniques Naive Bayes (NB) based on Hive and Decision Tree (DT) based on Spark to predict bug fix time of a reported bug. The experimental result is validated on 1,23,849 bug reports of Eclipse and 67,178 bug reports of Mozilla projects. The experimental evaluation has been validated on accuracy performance of bug fix time prediction. We observed that the proposed approach improves the accuracy as compared with work mentioned in Panjer (Proceedings of the fourth international workshop on mining software repositories, pp 1–4, 2007) [20].

Bug severity defines that to what extent the bug influence the software. Bug reports are misclassified affecting the performance of prediction and lead to biasness. Multitude relevant and irrelevant bugs are reported through bug-tracking systems, and it becomes necessary for the developer to give precedence to the bugs reported. The critical bugs need to be fixed immediately, and minor bugs can be fixed later on the basis of available resources. In this paper, we define different severity levels and assort them on the basis of their severity levels. It becomes problematic to assort tons of bugs manually, so we have used text mining approach to congregate words pointing severity of the reports obtained from Bugzilla for different components of ECLIPSE. The TF-IDF method is used to extract features and make dictionary of critical words. We have adopted neural network for the classification of bug reports and measured its performance.

Introduction: The present research was conducted at the University of Delhi, India in 2017. Methods: We develop a software reliability growth model to assess the reliability of software products released in multiple versions under limited availability of resources and time. The Fault Reduction Factor (frf) is considered to be constant in imperfect debugging environments while the rate of fault removal is given by Delayed S-Shaped model. Results: The proposed model has been validated on a real life four-release dataset by carrying out goodness of fit analysis. Laplace trend analysis was also conducted to judge the trend exhibited by data with respect to change in the system’s reliability. Conclusions: A number of comparison criteria have been calculated to evaluate the performance of the proposed model relative to only time-based multi-release Software Reliability Growth Model (srgm). Originality: In general, the number of faults removed is not the same as the number of failures experienced in given time intervals, so the inclusion of frf in the model makes it better and more realistic. A paradigm shift has been observed in software development from single release to multi release platform. Limitations: The proposed model can be used by software developers to take decisions regarding the release time for different versions, by either minimizing the development cost or maximizing the reliability and determining the warranty policies.

Fibroadenoma is a common abnormality which every surgeon has been exposed to, and there are several international guidelines regarding its management. However giant fibroadenomas, especially in the premenarche setting has been a rare occurrence, even for the experienced surgeon. Various reports have shown that we need to treat this condition more aggressively than the normal fibroadenoma, and issues of cosmesis in a developing breast along with the aim to preserve lactation functionality becomes an issue. Since these cases remain a single life time experience for most surgeons, there is a sparsity of treatment protocols even in literature. Through this paper we hope to shed some valuable insight to this rare disorder and help surgeon colleagues, when dealing with similar cases.

It is a challenge for developers to attain the desirable reliability for a software system considering the users and development team's requirements simultaneously. In our present work, we have inc...