Measurement and Analysis in CMMI with Six Sigma Methodology and ISO/IEC/IEEE 15939

  • Charles Shalimar Felippe da Silva Escola Preparatória de Cadetes do Ar
  • Marcelo Silva de Oliveira Universidade Federal de Lavras
Keywords: CMMI, Statistics, Six Sigma, ISO/IEC/IEEE 15939, Software Process

Abstract

Based on the premise that the quality of a software product is mostly the result of the quality of the process in which it is developed, models for the improvement of the process of software have been developed. The measurement and analysis for models assume great importance, because the evaluation of the relationship between the capacity (estimated results) and the performance (observed results) of a process is important so that it can be improved. CMMI is one of the more used models, having a great experience with success in the industry. CMMI do not indicate the measurement system to work and do not indicate its implementation. Six Sigma methodology conjugated to recommendations of ISO/IEC/IEEE 15939 aid CMMI in construction and implementation of that measurement system, as demonstrated by a case study that presented as results the indication of actions for the improvement of the software process.

Author Biographies

Charles Shalimar Felippe da Silva, Escola Preparatória de Cadetes do Ar

Doutorando no Departamento de Estatística (DES) da Universidade Federal de Lavras (UFLA)

Linhas de pesquisa: Estatística Aplicada em Gestão da Qualidade e Geoestatística

Marcelo Silva de Oliveira, Universidade Federal de Lavras

Professor Titular - Departamento de Estatística (DES) da Universidade Federal de Lavras (UFLA)

Linhas de pesquisa: Estatística Aplicada em Gestão da Qualidade e Estatística Espacial/Geoestatística

References

CMMI PRODUCT TEAM. CMMI for Development, Version 1.3. Pittsburgh: Software Engineering Institute, Carnegie Mellon University, 2010. Disponível em: http://www.sei.cmu.edu/. Acesso em: 04 jul. 2014.

IEEE. IEEE Standard Adoption of ISO/IEC 15939:2007: Systems and software engineering – Measurement process. New York: IEEE, 2009. 38 p.

KAN, S.H. Metrics and models in software quality engineering. Reading: Addison-Wesley, 1995. 344 p.

LibreOffice: The Document Foundation. Disponível em: http://www.libreoffice.org/. Acesso em: 08 de dezembro de 2014.

PAULA FILHO, W.P. Engenharia de software: fundamentos, métodos e padrões. Rio de Janeiro: LTC, 2001. 584 p.

PAULK, M.C.; WEBER, C.V.; CURTIS, B.; CHRISSIS, M.B. The Capability Maturity Model: guidelines for improving the software process. Reading: Addison-Wesley, 1994. 441 p.

PSM Support Center. PSM – Practical Software e Systems Measurement. Disponível em: http://www.psmsc.com. Acesso em: 10 jul. 2014.

R CORE TEAM. R: A language and environment for statistical computing. Vienna: R foundation for Statistical Computing, 2017. Disponível em: http://www.r-project.org. Acesso em: 13 jun. 2014.

ROTONDARO, R.G.; RAMOS, A.W.; RIBEIRO, C.O.; MIYAKE, D.I.; NAKANO, D.; LAURINDO, F.J.B.; HO, L.L.; CARVALHO, M.M. DE.; BRAZ, M.A.; BALESTRASSI, P.P. Seis Sigma: estratégia gerencial para a melhoria de processos, produtos e serviços. São Paulo: Atlas, 2002. 375 p.

SALVIANO, C.F. Uma Proposta Orientada a Perfis de Capacidade de Processo para Evolução da Melhoria de Processo de Software. 2006. 246 p. Tese (Doutorado em Engenharia Elétrica e de Computação) – Universidade Estadual de Campinas, Campinas, 2006.

Published
06-01-2023
Section
Applied Statistics