Prediction of software quality based on variables from the development process

  • Authors:

  • Hércules Antonio do Prado;Fábio Bianchi Campos;Edilson Ferneda;Nildo Nunes Cornelio;Aluizio Haendchen Filho

  • Affiliations:

  • Graduate Program on Knowledge and IT Management, Catholic University of Brasilia, Brasília, DF, Brazil,Embrapa - Management and Strategy Secretariat, Brasília, DF, Brazil;Graduate Program on Knowledge and IT Management, Catholic University of Brasilia, Brasília, DF, Brazil,Data Processing Center of the Brazilian Senate, Brasília, DF, Brazil;Graduate Program on Knowledge and IT Management, Catholic University of Brasilia, Brasília, DF, Brazil;Federal Bureau of Data Processing, Brasília, DF, Brazil,Centro Universitário do Distrito Federal - UDF, Brasília, DF, Brazil;UNIDAVI - Universidade para o Desenvolvimento do Alto Vale do Itajaí, Rio do Sul, Santa Catarina, Brazil

  • Venue:
  • KES'12 Proceedings of the 16th international conference on Knowledge Engineering, Machine Learning and Lattice Computing with Applications
  • Year:
  • 2012

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Abstract

Since the arising of software engineering many efforts have been devoted to improve the software development process. More recently, software quality has received attention from researchers due to the importance that software has gained in supporting all levels of the organizations. New methods, techniques, and tools were created to increase the quality and productivity of the software development process. Approaches based on the practitioners' experience, for example, or on the analysis of the data generated during the development process, have been adopted. This paper follows the second path by applying data mining procedures to figure out variables from the development process that most affect the software quality. The premise is that the quality of decision making in management of software projects is closely related to information gathered during the development process. A case study is presented in which some regression models were built to explore this idea during the phases of testing, approval, and production. The results can be applied, mainly, to help the development managers in focusing those variables to improve the quality of the software as a final product.