A Risk Management Model for Software Projects with Distributed Teams
DOI:
https://doi.org/10.5753/isys.2020.536Keywords:
Risk Management, Risk Identification, Risk Response, Risk Prediction, Distributed Software DevelopmentAbstract
The advance of business globalization in recent years is reflected in the area of information systems. Distributed software development (DDS) arises as an alternative that provides a global presence to companies, bringing their teams closer to this new reality. DDS has benefits having teams located in different geographic locations but can also provide to greater risk occurring in projects due to the greater complexity of coordination and communications among their members. Proper risk management through project history analysis decreases the occurrence of planning deviations from project time, cost, and quality. Understanding the benefits of proper risk management discipline practice, this article proposes the Átropos model to assist teams to identify and monitor risks at different points in the life cycle of projects. The work was evaluated by conducting a case study in a distributed software team, with a historical database containing 463 projects developed during the years 2017 and 2018.
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References
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Audy, Jorge; Prikladnicki, Rafael. (2007). Desenvolvimento Distribuído de Software. 1 ed. Elsevier. Rio de Janeiro, Brasil, 232pp.
Barbosa, J. L. V. (2015). Ubiquitous Computing: Applications and Research Opportunities (Invited Talk). VI IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Madurai, India, p.1–8. Disponível: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7435625. Acesso: 22/09/2018.
Bradner, E.; Mark, G.; Hertel, T. D. (2005). Team size and technology fit: participation, Awareness,and rapport in distributed teams, In: IEEE Transactions on Professional Communication, vol. 48, no. 1, pp. 68-77. Doi: 10.1109/TPC.2004.843299
Calefato, F.; Ebert, C. (2019). Agile Collaboration for Distributed Teams. In: IEEE Software, v. 36, p. 72–78.
Dey, Anind K. (2001). Understanding and Using Context, In: Personal and Ubiquitous Computing, Vol. 5, pp. 4-7. Doi: 10.1007/s007790170019.
Engeström, Y. (2014). Learning by expanding: An activity theoretical approach to developmental research. Ed. Cambridge University Press, 338pp.
Engeström, Y.; Sannino, A. (2011). Discursive manifestations of contradictions in organizational change efforts: A methodological framework, In: Journal of Organizational Change Management, v. 24, n. 3, p. 368–387.
Fan, Zhi-Ping; Yong-Hai, Li; Zhang, Yao. (2015). Generating project risk response strategies based on CBR: A case study, In: Expert Systems with Applications. pp 2870–2883. Doi: 10.1016/j.eswa.2014.11.034.
Fang, Chao; Marle, Franck. (2012). A simulation-based risk network model for decision support in project risk management, In: Decision Support Systems. pp 635–644. Doi: 10.1016/j.dss.2011.10.021.
Filippetto, Alexsandro; Barbosa, Jorge; Francisco, Rosemary; Klein, Amarolinda. (2016). A Project Management Model based on an Activity Theory Ontology, In: Conferência Latinoamericana de Informática.
Gerhardt, Tatiana Engel; Silveira, Denise Tolfo. (2009). “Métodos de Pesquisa”, 1 ed. UFRGS, Porto Alegre, Brasil, 120pp.
Google Cloud Natural Language API Documentation | Google Cloud Natural Language API | Google Cloud ([S.d.]). Disponível: https://cloud.google.com/natural-language/docs/classifying-text. Acesso: 09/02/2019.
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Joia, L.; Soler, A.; Bernat, G.; Rabechini, R. (2013). Gerenciamento de riscos em projetos. Ed. FGV, São Paulo, Brasil, 172pp.
Knappmeyer, M.; Kaini, S. L.; Reetz, E. S.; Backer, N.; Tonies, R. (2013). Survey of Context Provisioning Middleware. In: IEEE Communications Surveys & Tutorials. pp. 1492–1519. Doi: 10.1109/SURV.2013.010413.00207.
Leontiev, A. N. (2019). Activity, Consciousness, and Personality. [s.l.] Prentice-Hall. Disponível: http://www.marxists.org/archive/leontev/works/1978/index.htm. Acesso: 08/01/2019.
PMBOK. (2017). Project Management Institute. Um Guia do Conhecimento em Gerenciamento de Projetos (Guia PMBOK), 6th ed. Newtown Square, PA, EUA, 762pp.
Pressman, Roger S.; Maxim, Bruce R. (2016). Engenharia de Software – Uma Abordagem Profissional, 8 ed. Grupo A Educação, São Paulo, Brasil, 968pp.
Project Management Institute. (2016) Practice Standard for Project Risk Management. Newtown Square, PA, EUA, 116pp.
Qazi, Abroon; Quigley, John; Dickson, Alex; Kirytopoulos, Konstantinos. (2016). Project Complexity and Risk Management (ProCRiM): Towards modelling project complexity driven risk paths in contruction projects, In: International Journal of Project Management. Doi: 10.1016/j.ijproman.2016.05.008.
Rosa, João H. da; Barbosa, Jorge L. V.; Ribeiro, Giovane D. (2016). ORACON: An Adaptive Model for Context Prediction, In: International Journal of Expert Systems with Applications. Pp. 56-70. Doi: 10.1016/j.eswa.2015.09.016.
Shrivastava, S. and Rathod, U. (2014). Categorization of risk factors for distributed agile projects. In: IEEE Software. Doi: 10.1016/j.infsof.2014.07.007.
Sommerville, Ian. (2015). “Engenharia de Software”, 10 ed. Pearson Addison-Wesley, São Paulo, Brasil, 552pp.
Sulaman, Sardar Muhammad; Weyns, Kim; Höst, Martin. (2013). A review of research on risk analysismethodos for IT systems. roceedings of the 17th International Conference on Evaluation and Assessment in Software Engineering. Doi: 10.1145/2460999.2461013
Tianyin, P. (2011). Development of software project risk management model review. In IEEE Software. Doi: 10.1109/AIMSEC.2011.6011139.
Vygotsky, L. S. (2015). A formação social da mente. 7. ed. Martins Fontes, São Paulo, Brasil, 224pp: Martins Fontes.
Yang, Kai-Cheng; Varol, Onur; Davis, Clayton A.; Ferrara, Emilio; Flammini, Alessandro; Menczer, Filippo. (2019). Arming the public artificial intelligence to counter social bots, In: Human Behavior and Emerging Technologies. Doi: 10.1002/hbe2.115.
Zhang, Yao. (2016). Selecting risk response strategies considering project risk interdependence, In: International Journal of Project Management. Doi: 10.1016/j.ijproman.2016.03.001.
Zhang, Yao; Fan, Zhi-Ping. (2014). An optimization method for selecting project risk response strategies, In: International Journal of Project Management. pp 412–422. Doi: 10.1016/j.ijproman.2013.06.006.
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Published
2020-01-06
How to Cite
Filippetto, A. S., Lima, R., & Barbosa, J. (2020). A Risk Management Model for Software Projects with Distributed Teams. ISys - Brazilian Journal of Information Systems, 13(1), 114–143. https://doi.org/10.5753/isys.2020.536
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Regular articles
