Predicting Defects in Software Using Grammar-Guided Genetic Programming

Authors:
Athanasios Tsakonas;Georgios Dounias
Affiliations:
Department of Finance and Management Engineering, University of the Aegean, Chios, Greece;Department of Finance and Management Engineering, University of the Aegean, Chios, Greece
Venue:
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Year:
2008

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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.