Tsakonas, A. and Dounias , G., 2008. Application of Genetic Programming in Software Engineering Empirical Data Modelling. In: ICSOFT 2008: Proceedings of the Third International Conference on Software and Data Technologies. Porto, Portugal: INSTICC, pp. 295-300.
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Research in software engineering data analysis has only recently incorporated computational intelligence methodologies. Among these approaches, genetic programming retains a remarkable position, facilitating symbolic regression tasks. In this paper, we demonstrate the effectiveness of the genetic programming paradigm, in two major software engineering duties, effort estimation and defect prediction. We examine data domains from both the commercial and the scientific sector, for each task. The proposed model is proved superior to past literature works.
|Item Type:||Book Section|
|Additional Information:||ICSOFT 2008, 5-8 July 2008 Porto, Portugal|
|Uncontrolled Keywords:||artificial intelligence; computational intelligences; computer programming; data domains; data mining; decision support systems; defect prediction; defect predictions; effort estimation; effort estimations; empirical datums; engineering research; forecasting; genetic algorithms; genetic programming; information management; programming paradigms; software engineering; software engineering datums; symbolic regressions|
|Subjects:||Technology > Engineering > Electrical and Electronic Engineering|
|Group:||School of Design, Engineering & Computing > Smart Technology Research Centre|
|Deposited By:||Dr Athanasios Tsakonas LEFT|
|Deposited On:||25 May 2011 15:56|
|Last Modified:||07 Mar 2013 15:44|
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