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A Review Report on Requirements Analysis with Data Mining
  • Faizan Berlas
Faizan Berlas
Virtual University of Pakistan

Corresponding Author:[email protected]

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Abstract

 Software requirements engineering is the process of eliciting, analyzing, negotiating, specifying, documenting, and validating software requirements. These requirements are gathered from user needs, stakeholder needs, domain information, existing system information, organizational standards, and external regulations. Traditionally, the requirement engineering process has been driven by stakeholdersâ\euro™ needs. However, the advent of the Internet of Things (IoT) devices, mobile devices, social networks, and other big data technologies have caused a shift from the traditional mode of the requirements acquisition process to new data-driven and automatic modes of requirement elicitation by utilizing data mining techniques. The traditional methodologies of requirement engineering processes are inadequate for modern-day software applications due to their inability to effectively capture user requirements from the ever-increasing volume of data, customer requirements, and feedback. Consequently, the utilization of data mining techniques is gaining popularity in the field of requirement engineering. These techniques are employed to extract valuable insights from data and elicit customer requirements, providing a more robust approach to addressing the challenges posed by modern software development. This research paper comprehensively reviews various data mining techniques and methodologies used for gathering, eliciting, and analyzing software requirements. It offers valuable insights into the significant areas of data mining, requirements analysis, and elicitation that have undergone extensive research in recent years. By providing a thorough understanding of requirements engineering with data mining, the paper serves as a valuable resource for researchers venturing into the realm of requirement analysis and elicitation with data mining and seeking potential avenues for future research.Â