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    Perceptions, Expectations and Implementations of Big Data in Public Sector
    (Ieee, 2018) Dogdu, Erdogan; Ozbayoglu, Murat; Yazici, Ali; Karakaya, Ziya
    Big Data is one of the most commonly encountered buzzwords among IT professionals nowadays. Technological advancements in data acquisition, storage, telecommunications, embedded systems and sensor technologies resulted in huge inflows of streaming data coming from variety of sources, ranging from financial streaming data to social media tweets, or wearable health gadgets to drone flight logs. The processing and analysis of such data is a difficult task, but as appointed by many IT experts, it is crucial to have a Big Data Implementation plan in today's challenging industry standards. In this study, we performed a survey among IT professionals working in the public sector and tried to address some of their implementation issues and their perception of Big Data today and their expectations about how the industry will evolve. The results indicate that most of the public sector professionals are aware of the current Big Data requirements, embrace the Big Data challenge and are optimistic about the future.
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    Article
    Citation - WoS: 20
    Citation - Scopus: 25
    Quantitative Quality Evaluation of Software Products by Considering Summary and Comments Entropy of a Reported Bug
    (Mdpi, 2019) Kumari, Madhu; Misra, Ananya; Misra, Sanjay; Fernandez Sanz, Luis; Damasevicius, Robertas; Singh, V. B.
    A software bug is characterized by its attributes. Various prediction models have been developed using these attributes to enhance the quality of software products. The reporting of bugs leads to high irregular patterns. The repository size is also increasing with enormous rate, resulting in uncertainty and irregularities. These uncertainty and irregularities are termed as veracity in the context of big data. In order to quantify these irregular and uncertain patterns, the authors have appliedentropy-based measures of the terms reported in the summary and the comments submitted by the users. Both uncertainties and irregular patterns have been taken care of byentropy-based measures. In this paper, the authors considered that the bug fixing process does not only depend upon the calendar time, testing effort and testing coverage, but it also depends on the bug summary description and comments. The paper proposed bug dependency-based mathematical models by considering the summary description of bugs and comments submitted by users in terms of the entropy-based measures. The models were validated on different Eclipse project products. The models proposed in the literature have different types of growth curves. The models mainly follow exponential, S-shaped or mixtures of both types of curves. In this paper, the proposed models were compared with the modelsfollowingexponential, S-shaped and mixtures of both types of curves.