Word Health Organization declared coronavirus disease 2019 (COVID-19) as pandemic on 11 M arch 2020. After that on 14 M arch 2020 the M inistry of Home Affairs, India decided to treat COVID-19 as a "notified disaster" due to the spurt in the cases related to coronavirus in the country, leading to a complete shut down from 24 M arch 2020. This has affected all sectors of the country including the education sector. The near-total closure of schools, colleges, and universities has disrupted academic activities at various levels. The objective of this online survey study is to understand the day to day living, activities, learning styles, and mental health of young students of India during this unprecedented crisis and assess how they are adapting to the new e-learning styles and how they are managing their social lives.

Purpose -The purpose of this research is to incorporate the exponentiated Weibull testing-effort functions into software reliability modeling and to estimate the optimal software release time. Design/methodology/approach -This paper suggests a software reliability growth model based on the non-homogeneous Poisson process (NHPP) which incorporates the exponentiated Weibull (EW) testing-efforts. Findings -Experimental results on actual data from three software projects are compared with other existing models which reveal that the proposed software reliability growth model with EW testing-effort is wider and effective SRGM. Research limitations/implications -This paper presents a SRGM using a constant error detection rate per unit testing-effort. Practical implications -Software reliability growth model is one of the fundamental techniques to assess software reliability quantitatively. The results obtained in this paper will be useful during the software testing process. Originality/value -The present scheme has a flexible structure and may cover many of the earlier results on software reliability growth modeling. In general, this paper also provides a framework in which many software reliability growth models can be described.

This paper presents an in-depth understanding of Availability, which is one of the important pillars of Information Security and yet is not taken too seriously while talking about the security of an information system. The paper highlights the importance of Availability w.r.t. Security of information and the other attributes of security and also gives a realistic shape to the existing CIA triad security model. An in-depth understanding of the various factors that can impact the Availability of an information system (Software, Hardware and Network) is given. The paper also gives a categorization of the type of Availability that a system can have. The paper also explains the relation between Availability and other security attributes and also explains through what issues an information system may go while providing Availability.

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PurposeThe purpose of this research paper is to discuss a software reliability growth model (SRGM) based on the non‐homogeneous Poisson process which incorporates the Burr type X testing‐effort function (TEF), and to determine the optimal release‐time based on cost‐reliability criteria.Design/methodology/approachIt is shown that the Burr type X TEF can be expressed as a software development/testing‐effort consumption curve. Weighted least squares estimation method is proposed to estimate the TEF parameters. The SRGM parameters are estimated by the maximum likelihood estimation method. The standard errors and confidence intervals of SRGM parameters are also obtained. Furthermore, the optimal release‐time determination based on cost‐reliability criteria has been discussed within the framework.FindingsThe performance of the proposed SRGM is demonstrated by using actual data sets from three software projects. Results are compared with other traditional SRGMs to show that the proposed model has a fairly better prediction capability and that the Burr type X TEF is suitable for incorporating into software reliability modelling. Results also reveal that the SRGM with Burr type X TEF can estimate the number of initial faults better than that of other traditional SRGMs.Research limitations/implicationsThe paper presents the estimation method with equal weight. Future research may include extending the present study to unequal weight.Practical implicationsThe new SRGM may be useful in detecting more faults that are difficult to find during regular testing, and in assisting software engineers to improve their software development process.Originality/valueThe incorporated TEF is flexible and can be used to describe the actual expenditure patterns more faithfully during software development.