Home / Journals / CSSE / Vol.33, No.3, 2018
  • Open Access

    ARTICLE

    A Risk Poker Based Testing Model for Scrum

    Siti Noor Hasanah Ghazali1, Siti Salwah Salim1,*, Irum Inayat2, Siti Hafizah Ab Hamid1
    Computer Systems Science and Engineering, Vol.33, No.3, pp. 169-185, 2018, DOI:10.32604/csse.2018.33.169
    Abstract In agile software development, project estimation often depends on group discussion and expert opinions. Literature claims that group discussion in risk analysis helps to identify some of the crucial issues that might affect development, testing, and implementation. However, risk prioritization often relies on individual expert judgment. Therefore, Risk Poker, a lightweight risk-based testing methodology in which risk analysis is performed through group discussion that outperforms the individual analyst’s estimation is introduced in agile methods. Keeping in view aforementioned benefits Risk Poker can offer, unfortunately, no study has been conducted to empirically prove its ability to improve the testing process to… More >

  • Open Access

    ARTICLE

    Sentiment Analysis System in Big Data Environment

    Wint Nyein Chan1, Thandar Thein2
    Computer Systems Science and Engineering, Vol.33, No.3, pp. 187-202, 2018, DOI:10.32604/csse.2018.33.187
    Abstract Nowadays, Big Data, a large volume of both structured and unstructured data, is generated from Social Media. Social Media are powerful marketing tools and social big data can offer the business insights. The major challenge facing social big data is attaining efficient techniques to collect a large volume of social data and extract insights from the huge amount of collected data. Sentiment Analysis of social big data can provide business insights by extracting the public opinions. The traditional analytic platforms need to be scaled up for analyzing a large volume of social big data. Social data are by nature shorter… More >

  • Open Access

    ARTICLE

    Forensic Investigation Through Data Remnants on Hadoop Big Data Storage System

    Myat Nandar Oo1, Sazia Parvin2, Thandar Thein3
    Computer Systems Science and Engineering, Vol.33, No.3, pp. 203-217, 2018, DOI:10.32604/csse.2018.33.203
    Abstract Forensic examiners are in an uninterrupted battle with criminals in the use of Big Data technology. The underlying storage system is the main scene to trace the criminal activities. Big Data Storage System is identified as an emerging challenge to digital forensics. Thus, it requires the development of a sound methodology to investigate Big Data Storage System. Since the use of Hadoop as Big Data Storage System continues to grow rapidly, investigation process model for forensic analysis on Hadoop Storage and attached client devices is compulsory. Moreover, forensic analysis on Hadoop Big Data Storage System may take additional time without… More >

  • Open Access

    ARTICLE

    Integrating a Decision Tree Perspective at the Operational-Level of BPM+

    Ahmad Alomari1,∗, Alain April1, Carlos Monsalve2, Amjad Gawanmeh3
    Computer Systems Science and Engineering, Vol.33, No.3, pp. 219-227, 2018, DOI:10.32604/csse.2018.33.219
    Abstract Decision trees are among the best-known decision-making techniques and have been used extensively for both data analysis and predictive modeling. BPM+ is a novel process modeling approach that helps represent business process models in a consistent and structured way to meet different stakeholders’ process representation needs. This paper reports on the outcomes of an ontological analysis of the potential use of decision-tree representations as a new BPM+ perspective for the operational level of abstraction. This new perspective effectively demonstrates how a specialized/operational BPM stakeholder perspective can be used to improve the existing organizational business process model repository. More >

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