Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/37419

TítuloEstimating risk management in software engineering projects
Autor(es)Santos, Jaime
Belo, O.
Palavras-chaveSoftware engineering
Project management
Data mining
Effort estimation
Risk management
Project Success Classification
Data2013
EditoraSpringer
RevistaLecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Resumo(s)Independently from the nature of a project, process management variables like cost, quality, schedule, and scope are critical decision factors for a good and successful execution of a project. In software engineering, project planning and execution are highly influenced by the creative nature of all the individuals involved with the project. Thus, managing the risks of different project stages is a key task with extreme importance for project managers (and sponsors) that should be focused on control and monitoring effectively the referred variables, as well as all the others concerned with their context. In this work, we used a small “cocktail” of data mining techniques and methods to explore potential correlations and influences contained in some of the most relevant parameters related to experience, complexity, organization maturity and project innovation in Software Engineering, developing in a model that could be deployed in any project management process, assisting project managers in planning and monitoring the state of one project (or program) under its supervision.
TipoArtigo em ata de conferência
DescriçãoPublicado em "Advances in data mining: applications and theoretical aspects. Volume 7987 of the series Lecture notes in computer science"
URIhttps://hdl.handle.net/1822/37419
ISBN978-3-642-39735-6
978-3-642-39736-3
DOI10.1007/978-3-642-39736-3_7
ISSN0302-9743
Arbitragem científicayes
AcessoAcesso restrito UMinho
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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