Bioinformatics Approach to Data Mining of Software Bases

G. Stiglic, P. Kokol (Slovenia), and L. Lhotska (Czech Republic)


Artificial intelligence, machine learning, multi-agent systems, software fault prediction.


In this paper we propose a new method inspired by a multi-agent based system that was initially used for identification of significant genes in microarray databases. Gene subset selection is a common problem in the filed of bioinformatics. If we regard the software measurements values of a software module as a genome of that module, and the real world dynamic characteristic of that module as its phenotype (i. e. failures as a disease symptoms) we can borrow the established bioinformatics methods in the manner first to predict the module behaviour and second to data mine the relations between metrics and failures.

Important Links:

Go Back