Avaliando uma ferramenta baseada em dados históricos para auxiliar o gerenciamento de riscos: um estudo de caso em projetos de software

Autores

DOI:

https://doi.org/10.5585/gep.v14i2.24431

Palavras-chave:

Gestão de Riscos, Projetos de software, Grupo focal, Estudo de caso, Dados históricos, Rede bayesiana

Resumo

Um risco é um evento ou condição incerta que, se ocorrer, afeta os objetivos dos projetos. O gerenciamento de riscos é uma atividade custosa e passível de erros porque os riscos são eventos abstratos e subjetivos. O objetivo deste artigo é apresentar uma ferramenta para auxiliar no gerenciamento de riscos em projetos de software. O procedimento metodológico adotado foi um estudo de caso, colhendo informações por meio de grupos focais. Para avaliar a ferramenta, foram realizados experimentos com equipes reais em projetos de software. Além disso, para verificar a percepção dos profissionais, aplicamos um questionário baseado na metodologia TAM. A ferramenta denominada Risk Control propõe-se a tornar o gerenciamento de risco mais objetivo e sistemático, diminuindo a subjetividade na tomada de decisão. Os resultados apontaram para a utilidade da abordagem na identificação e no monitoramento de riscos. Porém, os profissionais fizeram ressalvas sobre a aplicabilidade em relação à mensuração de riscos. As contribuições da ferramenta são as inferências probabilísticas utilizando Rede Bayesiana, oferecendo respostas adaptadas às novas entradas assim que são introduzidas.

Referências

Arumugam, C., Kameswaran, S., & Kaliamourthy, B. (2017, November). Global software development: A design framework to measure the risk of the global practitioners. In Proceedings of the 7th International Conference on Computer and Communication Technology (pp. 1-8). https://doi.org/10.1145/3154979.3154983.

Boehm, B. (1989, September). Software risk management. In European software engineering conference (pp. 1-19). Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-51635-2_29.

Chrissis, M. B., Konrad, M., & Shrum, S. (2011). CMMI for development: guidelines for process integration and product improvement. Pearson Education. Link: https://resources.sei.cmu.edu/library/asset-view.cfm?assetid=31054.

Dantas, E., Sousa Neto, A., Perkusich, M., Almeida, H., & Perkusich, A. (2021). Using Bayesian Networks to Support Managing Technological Risk on Software Projects. In Anais do I Workshop Brasileiro de Engenharia de Software Inteligente, (pp. 1-6). Porto Alegre: SBC. https://doi.org/10.5753/ise.2021.17277.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340. https://doi.org/10.2307/249008

Hossain, E., Babar, M. A., Paik, H. Y., & Verner, J. (2009, December). Risk identification and mitigation processes for using scrum in global software development: A conceptual framework. In 2009 16th Asia-Pacific Software Engineering Conference (pp. 457-464). IEEE. https://doi.org/10.1109/APSEC.2009.56.

International Organization for Standardization (2009). ISO 31000: Risk management-Principles and guidelines. Geneva: ISO. Link: https://www.iso.org/iso-31000-risk-management.html.

Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2015). Likert scale: Explored and explained. British journal of applied science & technology, 7(4), 396. https://doi.org/10.9734/BJAST/2015/14975.

Khanna, E., Popli, R., & Chauhan, N. (2021, August). Artificial Intelligence based Risk Management Framework for Distributed Agile Software Development. In 2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) (pp. 657-660). IEEE. https://doi.org/10.1109/SPIN52536.2021.9566000.

Kerzner, H. (2017). Project management: a systems approach to planning, scheduling, and controlling. John Wiley & Sons. Link: http://www.mim.ac.mw/books/Kerzner's%20Project%20Management%20A%20Systems%20Approach...10thed.pdf.

Lee, O. K., & Baby, D. V. (2013). Managing dynamic risks in global it projects: Agile risk-management using the principles of service-oriented architecture. International Journal of Information Technology & Decision Making, 12(06), 1121-1150. https://doi.org/10.1142/S0219622013400117.

Leitch, M. (2010). ISO 31000: 2009-The new international standard on risk management. Risk analysis, 30(6), 887. https://doi.org/10.1111/j.1539-6924.2010.01397.x.

Meirinhos, M., & Osório, A. (2010). O estudo de caso como estratégia de investigação em educação. EduSer, 2(2). https://doi.org/10.34620/eduser.v2i2.24.

Mendes, E., Rodriguez, P., Freitas, V., Baker, S., & Atoui, M. A. (2018). Towards improving decision making and estimating the value of decisions in value-based software engineering: the VALUE framework. Software Quality Journal, 26(2), 607-656. https://doi.org/10.1007/s11219-017-9360-z.

Miguel, P. A. C. (2007). Estudo de caso na engenharia de produção: estruturação e recomendações para sua condução. Production, 17, 216-229. https://doi.org/10.1590/S0103-65132007000100015.

Odzaly¹, E. E., & Des Greer¹, D. S. (2014). Lightweight risk management in Agile projects. Link: https://www.academia.edu/download/70086054/Lightweight_Risk_Management_in_Agile_Pro20210921-30204-1ihxgi8.pdf

Odzaly, E. E., Greer, D., & Stewart, D. (2018). Agile risk management using software agents. Journal of Ambient Intelligence and Humanized Computing, 9, 823-841. https://doi.org/10.1007/s12652-017-0488-2.

PMI. (2019). Project management body of knowledge (pmbok® guide). In Project Management Institute (Vol. 11, pp. 7-8). Link: http://lms.aambc.edu.et:8080/xmlui/bitstream/handle/123456789/160/PROJECT%20MANAGEMENT%20BODY%20OF%20KNOWLEDGE%20(PMBOK%20GUIDE)%20(%20PDFDrive.com%20).pdf?sequence=1.

Purdy, G. (2010). ISO 31000: 2009—setting a new standard for risk management. Risk Analysis: An International Journal, 30(6), 881-886. https://doi.org/10.1111/j.1539-6924.2010.01442.x.

Rabbi, M. F., & Mannan, K. O. B. (2008, August). A review of software risk management for selection of best tools and techniques. In 2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (pp. 773-778). IEEE. https://doi.org/10.1109/SNPD.2008.127.

Rosenberger, P., & Tick, J. (2018, November). Suitability of PMBOK 6 th edition for agile-developed IT Projects. In 2018 IEEE 18th International Symposium on Computational Intelligence and Informatics (CINTI) (pp. 000241-000246). IEEE. https://doi.org/10.1109/CINTI.2018.8928226.

Russell, R. S., & Taylor-Iii, B. W. (2008). Operations management along the supply chain. John Wiley & Sons. Link: http://jtelen.free.fr/0MARINE%20bouquins/%5BRoberta_S._Russell,_Bernard_W._Taylor%5D_Operations(Bookos.org).pdf

Sasankar, A. B., & Chavan, V. (2011). SWOT analysis of software development process models. International Journal of Computer Science Issues (IJCSI), 8(5), 390.

Schwaber, K., & Sutherland, J. (2011). The scrum guide. Scrum Alliance, 21(19), 1. Link: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=cb1ce98a878d5d783cf8108b870d817853a01f6c#page=400.

Shull, F., Singer, J., & Sjøberg, D. I. (Eds.). (2007). Guide to advanced empirical software engineering. Springer Science & Business Media. https://doi.org/10.1007/978-1-84800-044-5.

Takagi, Y., Mizuno, O., & Kikuno, T. (2005). An empirical approach to characterizing risky software projects based on logistic regression analysis. Empirical Software Engineering, 10(4), 495-515. https://doi.org/10.1007/s10664-005-3864-z.

Tavares, B. G., da Silva, C. E. S., & de Souza, A. D. (2019). Risk management analysis in Scrum software projects. International Transactions in Operational Research, 26(5), 1884-1905. https://doi.org/10.1111/itor.12401.

Tomanek, M., & Juricek, J. (2015). Project risk management model based on PRINCE2 and SCRUM frameworks. arXiv preprint arXiv. Link: https://arxiv.org/abs/1502.03595

Ventura, M. M. (2007). O estudo de caso como modalidade de pesquisa. Revista SoCERJ, 20(5), 383-386. http://sociedades.cardiol.br/socerj/revista/2007_05/a2007_v20_n05_art10.pdf.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. https://doi.org/10.2307/30036540.

Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178. https://doi.org/10.2307/41410412.

Weber, K., Araújo, E., Rocha, A. R. C., Oliveira, K. M., Rouiller, A. C., von Wangenheim, C. G., ... & Yoshida, D. (2006, August). Melhoria de Processo do Software Brasileiro (MPS. BR): um programa mobilizador. In Proceedings of the XXXI Conferencia Latinoamericana de Informatica (CLEI 2006). Santiago, Chile: agosto. Link: https://www.softex.br/wp-content/uploads/2015/08/Artigo_CLEI-200611.pdf.

Xu, Z., Khoshgoftaar, T. M., & Allen, E. B. (2003). Application of fuzzy expert systems in assessing operational risk of software. Information and software technology, 45(7), 373-388. https://doi.org/10.1016/S0950-5849(03)00010-7.

Yin, R. K. (2015). Estudo de Caso-: Planejamento e métodos. Bookman editora. Link: https://edisciplinas.usp.br/mod/resource/view.php?id=3878524.

Publicado

2023-08-01

Como Citar

Dantas Filho, E., & França de Sousa Neto, A. (2023). Avaliando uma ferramenta baseada em dados históricos para auxiliar o gerenciamento de riscos: um estudo de caso em projetos de software. Revista De Gestão E Projetos, 14(2), 196–213. https://doi.org/10.5585/gep.v14i2.24431

Edição

Secção

Relatos Técnicos