2011
Bruno Lopes Dalmazo, Weverton Luis da Costa Cordeiro, Abraham Lincoln Rabelo de Sousa, Juliano Araujo Wickboldt, Roben Castagna Lunardi, Ricardo Luis dos Santos, Luciano Paschoal Gaspary, Lisandro Zambenedetti Granville, Claudio Bartolini, Marianne Hickey
Leveraging IT project lifecycle data to predict support costs Inproceedings
In: 12th IFIP/IEEE International Symposium on Integrated Network Management, IM 2011, Dublin, Ireland, 23-27 May 2011, pp. 249–256, IEEE, 2011, ISSN: 1573-0077.
Abstract Links BibTeX Tags: Bayesian Networks COBIT ITIL Project Management Project Suport Costs
@inproceedings{DBLP:conf/im/DalmazoCSWLSGGBH11,
title = {Leveraging IT project lifecycle data to predict support costs},
author = {Bruno Lopes Dalmazo and Weverton Luis da Costa Cordeiro and Abraham Lincoln Rabelo de Sousa and Juliano Araujo Wickboldt and Roben Castagna Lunardi and Ricardo Luis dos Santos and Luciano Paschoal Gaspary and Lisandro Zambenedetti Granville and Claudio Bartolini and Marianne Hickey},
url = {https://doi.org/10.1109/INM.2011.5990698},
doi = {10.1109/INM.2011.5990698},
issn = {1573-0077},
year = {2011},
date = {2011-01-01},
booktitle = {12th IFIP/IEEE International Symposium on Integrated Network Management, IM 2011, Dublin, Ireland, 23-27 May 2011},
pages = {249--256},
publisher = {IEEE},
abstract = {There is an intuitive notion that the costs associated with project support actions, currently deemed too high and increasing, are directly related to the effort spent during their development and test phases. Despite the importance of systematically characterizing and understanding this relationship, little has been done in this realm mainly due to the lack of proper tooling for both sharing information between IT project phases and learning from past experiences. To tackle this issue, in this paper we propose a solution that, leveraging existing IT project lifecycle data, is able to predict support costs. The solution has been evaluated through a case study based on the ISBSG dataset, producing correct estimates for more than 80% of the assessed scenarios.},
keywords = {Bayesian Networks, COBIT, ITIL, Project Management, Project Suport Costs},
pubstate = {published},
tppubtype = {inproceedings}
}
There is an intuitive notion that the costs associated with project support actions, currently deemed too high and increasing, are directly related to the effort spent during their development and test phases. Despite the importance of systematically characterizing and understanding this relationship, little has been done in this realm mainly due to the lack of proper tooling for both sharing information between IT project phases and learning from past experiences. To tackle this issue, in this paper we propose a solution that, leveraging existing IT project lifecycle data, is able to predict support costs. The solution has been evaluated through a case study based on the ISBSG dataset, producing correct estimates for more than 80% of the assessed scenarios.
Bruno Lopes Dalmazo, Abraham Lincoln Rabelo de Sousa, Weverton Luis da Costa Cordeiro, Juliano Araujo Wickboldt, Roben Castagna Lunardi, Ricardo Luis dos Santos, Luciano Paschoal Gaspary, Lisandro Zambenedetti Granville, Claudio Bartolini, Marianne Hickey
IT Project Variables in the Balance: A Bayesian Approach to Prediction of Support Costs Inproceedings
In: 25th Brazilian Symposium on Software Engineering, SBES 2011, Sao Paulo, Brazil, September 28-30, 2011, pp. 224–232, IEEE Computer Society, 2011, ISBN: 978-1-4577-2187-8.
Abstract Links BibTeX Tags: Bayesian Networks COBIT ITIL Project Management Project Suport Costs
@inproceedings{DBLP:conf/sbes/DalmazoSCWLSGGBH11,
title = {IT Project Variables in the Balance: A Bayesian Approach to Prediction of Support Costs},
author = {Bruno Lopes Dalmazo and Abraham Lincoln Rabelo de Sousa and Weverton Luis da Costa Cordeiro and Juliano Araujo Wickboldt and Roben Castagna Lunardi and Ricardo Luis dos Santos and Luciano Paschoal Gaspary and Lisandro Zambenedetti Granville and Claudio Bartolini and Marianne Hickey},
url = {https://doi.org/10.1109/SBES.2011.37},
doi = {10.1109/SBES.2011.37},
isbn = {978-1-4577-2187-8},
year = {2011},
date = {2011-01-01},
booktitle = {25th Brazilian Symposium on Software Engineering, SBES 2011, Sao Paulo, Brazil, September 28-30, 2011},
pages = {224--232},
publisher = {IEEE Computer Society},
abstract = {In the context of Information Technology (IT) project management, it is commonly accepted that the costs associated with support actions are strongly influenced by the effort spent during their development and test phases. Despite the importance of systematically characterizing and understanding this relationship, little has been done in this realm mainly due to the lack of proper mechanisms for both sharing information between IT project phases and learning from past experiences. To tackle this issue, we present a Bayesian model to perform support cost predictions based on data from software development and test phases. In addition, we present a qualitative and quantitative analysis of the model, in order to demonstrate its effectiveness and efficiency, and also discuss its potentialities and limitations.},
keywords = {Bayesian Networks, COBIT, ITIL, Project Management, Project Suport Costs},
pubstate = {published},
tppubtype = {inproceedings}
}
In the context of Information Technology (IT) project management, it is commonly accepted that the costs associated with support actions are strongly influenced by the effort spent during their development and test phases. Despite the importance of systematically characterizing and understanding this relationship, little has been done in this realm mainly due to the lack of proper mechanisms for both sharing information between IT project phases and learning from past experiences. To tackle this issue, we present a Bayesian model to perform support cost predictions based on data from software development and test phases. In addition, we present a qualitative and quantitative analysis of the model, in order to demonstrate its effectiveness and efficiency, and also discuss its potentialities and limitations.