@article{1571,
  author = {Md. Tajmilur Rahman, Al Abrar Hasan, Rashedur M Rahman, M A Matin},
  title = {Mining Bug Database for Detecting Potential Areas of Bug Occurence},
  journal = {International Journal of Information Studies},
  year = {2014},
  volume = {6},
  number = {1},
  doi = {},
  url = {https://www.dline.info/ijis/fulltext/v6n1/ijisv6n1_3.pdf},
  abstract = {Vulnerability issues are really important for any system, therefore, many testing approaches have been proposed so far. Recently, it is becoming more and more difficult to ignore the analysis of data for web applications specially the social
networking websites. In social networking communities, there are lot of public pages and public components where people might easily get access of the system inside. This paper aims to examine the classes of errors in a social networking site and propose clustering approach for identification of the potential areas of fault/error logs on social networking site.},
}