Comparative analysis of clustering algorithms applied to the classification of bugs

Authors:
Anderson Santana;Jackson Silva;Patrícia Muniz;Fabricio Araújo;Renata Maria Cardoso R. de Souza
Affiliations:
Informatics Center, Fedederal Universitity of Pernambuco, Recife, Pernambuco, Brazil;Informatics Center, Fedederal Universitity of Pernambuco, Recife, Pernambuco, Brazil;Informatics Center, Fedederal Universitity of Pernambuco, Recife, Pernambuco, Brazil;Informatics Center, Fedederal Universitity of Pernambuco, Recife, Pernambuco, Brazil;Informatics Center, Fedederal Universitity of Pernambuco, Recife, Pernambuco, Brazil
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Year:
2012

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Abstract

This paper presents a study of clustering algorithms in bug classification for a company from a database that contains a description each bug. It is made a comparison these algorithms using a sample of the database of this company. Considering that the classification will encourage the decision process of the organization as the result of the efficiency and reliability increase, this study will conduct an investigation to identify, among the techniques employed, one that will produce satisfactory results for the company, so to provide a set of information that are relevant to strategic decision making.