A model for dealing with epistemic uncertainties in agile software project management

• Ano de defesa: 2023
• Autor(a) principal: BARBOSA, Jefferson Ferreira
• Orientador(a): MOURA, Hermano Perrelli de
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Pernambuco
• Programa de Pós-Graduação: Programa de Pos Graduacao em Ciencia da Computacao
• País: Brasil
• Palavras-chave em Português: Engenharia de software e Linguagens de programação; Gerenciamento de projetos de software; Incerteza epistêmica; Quantificação da incerteza; Gestão ágil
• Link de acesso: https://repositorio.ufpe.br/handle/123456789/52022

Since agile methods began to be used for software development, project managers have been looking for ways to improve these projects. Agility coexists with uncertainty, as one of the agile project’s principles is the possibility of rapid change. Uncertainty quantification allows comparative purposes and evaluating alternative approaches to real-world problems in manag- ing uncertainty. Some recent studies show that current approaches to managing uncertainty organize known project information but give little or no indication of the unknown information or uncertainties associated with the project. These uncertainty management approaches do not consider the quantitative aspect of uncertainty management beyond the interrelationships between sources of uncertainty in software projects. This thesis aims to build a model to deal with epistemic uncertainties based on quantification approaches. In addition, it seeks to iden- tify interdependent relationships between sources of uncertainty in the agile management of software projects. The method used in this work was action research conducted to investigate the quantification of epistemic uncertainty in the real context of software engineering design. The author also conducted a quasi-systematic literature review to support action research searching for approaches to quantify epistemic uncertainty in software projects. The applica- tion of the method illustrates the benefit of applying uncertainty quantification approaches to reduce and prioritize epistemic uncertainties in software projects. Applying the above re- search methods resulted in the construction of a model to quantify epistemic uncertainty in software projects. This thesis also discusses the impact of a proposed model for dealing with epistemic uncertainty management. These results share findings that can help agile software teams improve their uncertainty handling.