EXTAMT: A systematic map to navigate the wide seas of factors affecting expert judgment software estimate

Autor(es)

Fernandes Matsubara, Patricia Gomes ^{[1, 2]} ; Gadelha, Bruno Freitas ^[1] ; Steinmacher, Igor ^{[3, 4]} ; Conte, Tayana Uchoa ^[1]

Afiliação do(s) autor(es)

^[1] Fed Univ Amazonas UFAM, Inst Comp, Manaus, Amazonas - Brazil

^[2] Fed Univ Mato Grosso do Sul UFMS, Fac Comp, Campo Grande, MS - Brazil

^[3] Fed Univ Technol Parana UTFPR, Curitiba, Parana - Brazil

^[4] Northern Arizona Univ NAU, Flagstaff, AZ - USA

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF SYSTEMS AND SOFTWARE; v. 185, MAR 2022.
• Citações Web of Science: 0

Resumo

Context: Software projects involve technical and managerial activities, including software estimation. Inaccurate estimates are harmful and improving estimation methods is not enough: we need to understand more of the factors that impact estimates. Objective: Our study aims to identify the existing evidence about the factors that affect estimates in software projects when using expert judgment. Method: We executed a Systematic Literature Mapping (SLM) based on database and snowballing searches, selecting papers by first reading their titles and abstracts and later reading the full text. Results: Researchers investigated a wide range of different factors employing mostly laboratory research strategies and relying primarily on differences of estimates and participants' perceptions to measure the factors' effects. Resulting from our analysis, we present the SEXTAMT (Software Estimates of eXperts: A Map of influencing facTors), a map of factors affecting estimates built on three dimensions: project/iteration phase, stakeholders, and type of effect. Conclusion: Over the years, researchers have investigated a varied set of factors. Many of them were explored in different studies, employing diverse research strategies. Such studies provide compelling evidence on the elements that influence expert judgment estimates, which can be used to assess and improve everyday estimation in the software industry. (C) 2021 Elsevier Inc. All rights reserved. (AU)

• Processo FAPESP: 20/05191-2 - INDEXAR: INDividualização da EXperiência de uso em ferramentas de apoio à Aprendizagem Remota
• Beneficiário: Tayana Uchôa Conte
• Modalidade de apoio: Auxílio à Pesquisa - Regular