Predicting Defects in Software Using Grammar-Guided Genetic Programming.

Tsakonas, A. and Dounias, G., 2008. Predicting Defects in Software Using Grammar-Guided Genetic Programming. In: Darzentas, J., Vouros , G., Vosinakis, S. and Arnellos, A., eds. Artificial Intelligence: Theories, Models and Applications: 5th Hellenic Conference on AI, SETN 2008, Syros, Greece, October 2-4, 2008, Proceedings. Berlin-Heidelberg: Springer-Verlag, pp. 413-418.

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Official URL: http://dx.doi.org/10.1007/978-3-540-87881-0_42

DOI: 10.1007/978-3-540-87881-0_42

Abstract

The knowledge of the software quality can allow an organization to allocate the needed resources for the code maintenance. Maintaining the software is considered as a high cost factor for most organizations. Consequently, there is need to assess software modules in respect of defects that will arise. Addressing the prediction of software defects by means of computational intelligence has only recently become evident. In this paper, we investigate the capability of the genetic programming approach for producing solution composed of decision rules. We applied the model into four software engineering databases of NASA. The overall performance of this system denotes its competitiveness as compared with past methodologies, and is shown capable of producing simple, highly accurate, tangible rules.

Item Type:Book Section
ISBN:978-3-540-87880-3
Series Name:Lecture Notes in Computer Science
Number:5138
Number of Pages:444
ISSN:0302-9743
Series Name:Lecture Notes in Computer Science
Uncontrolled Keywords:Software engineering, defect prediction, genetic programming.
Subjects:Generalities > Computer Science and Informatics > Artificial Intelligence
Group:School of Design, Engineering & Computing > Smart Technology Research Centre
ID Code:17873
Deposited By:Mrs Jean Harris
Deposited On:25 May 2011 15:03
Last Modified:07 Mar 2013 15:44

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