N. K. Nagwani and S. Verma, “Predictive Data Mining Model for Software Bug Estimation Using Average Weighted Similarity,” Proceedings of IEEE 2nd International Advance Computing Conference (IACC 2010), Patiala, 19-20 February 2010 pp. 373-378. doi:10.1109/IADCC.2010.5422923

has been cited by the following article:

• TITLE: Rank-Me: A Java Tool for Ranking Team Members in Software Bug Repositories

  AUTHORS: Naresh Kumar Nagwani, Shrish Verma

  KEYWORDS: Software Bug Repository; Team Member Rating; Rating Software Bugs; Team Member Scores in Bug Repositories

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.5 No.4, April 23, 2012

  ABSTRACT: In this paper a team member ranking technique is presented for software bug repositories. Member ranking is performed using numbers of attributes available in software bug repositories, and a ranked list of developers is generated who are participating in development of software project. This ranking is generated from the contribution made by the individual developers in terms of bugs fixed, severity and priority of bugs, reporting newer problems and comments made by the developers. The top ranked developers are the best contributors for the software projects. The proposed algorithm can also be used for classifying and rating the software bugs using the ratings of members participating in the software bug repository.