Kandregula Atchutanand, Kothalanka Amarendra


Data reduction for bug sorting aims to construct a small-scale still as elegant set of bug information by means that of removal of bug reports and words, that are redundant as an alternative non-informative. In our work, existing strategies of Instance choice was combined with feature choice to scale back information scale on bug dimension still as word dimension. To avoid wasting labour price of developers, information reduction meant for bug sorting has 2 goals like reducing information scale and rising accurateness of bug sorting.  Our work provides An approach to leverage strategies on processing to make reduced still as high-quality bug information in computer code development still as maintenance. to search out order of applying instance choice still as feature choice, we tend to do away with attributes from historical bug information sets and a prognosticative model was thought of for a modern bug information set. Our information reduction will effectively decrease the information scale and find higher the accuracy of bug sorting.


Data Reduction; Bug Triage; Bug Data; Data Processing; Software Development; Developers; Redundant; Feature Selection; Instance Selection; Word Dimension;


G. Jeong, S. Kim, and T. Zimmermann, “Improving bug triage with tossing graphs,” in Proc. Joint Meeting 12th Eur. Softw. Eng. Conf. 17th ACM SIGSOFT Symp. Found. Softw. Eng., Aug. 2009, pp. 111–120.

T. M. Khoshgoftaar, K. Gao, and N. Seliya, “Attribute selection and imbalanced data: Problems in software defect prediction,” in Proc. 22nd IEEE Int. Conf. Tools Artif. Intell., Oct. 2010, pp. 137–144.

T. Kohonen, J. Hynninen, J. Kangas, J. Laaksonen, and K. Torkkola, “LVQ_PAK: The learning vector quantization program package,” Helsinki Univ. Technol., Esbo, Finland, Tech. Rep. A30, 1996.

J. W. Park, M. W. Lee, J. Kim, S. W. Hwang, and S. Kim, “Costriage: A cost-aware triage algorithm for bug reporting systems,” in Proc. 25th Conf. Artif. Intell., Aug. 2011, pp. 139–144.

J. C. Riquelme, J. S. Aguilar-Ruız, and M. Toro, “Finding representative patterns with ordered projections,” Pattern Recognit., vol. 36, pp. 1009–1018, 2003.

M. Robnik-Sikonja and I. Kononenko, “Theoretical and empirical analysis of relieff and rrelieff,” Mach. Learn., vol. 53, no. 1/2, pp. 23–69, Oct. 2003.

Full Text: PDF


  • There are currently no refbacks.

Copyright © 2012 - 2020, All rights reserved.|

Creative Commons License
International Journal of Innovative Technology and Research is licensed under a Creative Commons Attribution 3.0 Unported License.Based on a work at IJITR , Permissions beyond the scope of this license may be available at