The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 29-754
Full Name: Vili Podgorelec
Position: Associate Professor
Age: ON
Sex: Male
Address: University of Maribor, FERI, Smetanova ulica 17, SI-2000 Maribor
Country: SLOVENIA
Tel: +386 2 220 7353
Tel prefix:
Fax: +386 2 220 7272
E-mail address: vili.podgorelec@uni-mb.si
Other E-mails:
Title of the Paper: Improved Mining of Software Complexity Data on Evolutionary Filtered Training Sets
Authors as they appear in the Paper: Vili Podgorelec
Email addresses of all the authors: vili.podgorelec@uni-mb.si
Number of paper pages: 10
Abstract: With the evolution of information technology and software systems, software reliability has become one of the most important topics of software engineering. As the dependency of society on software systems increase, so increases also the importance of efficient software fault prediction. In this paper we present a new approach to improving the classification of faulty software modules. The proposed approach is based on filtering training sets with the introduction of data outliers identification and removal method. The method uses an ensemble of evolutionary induced decision trees to identify the outliers. We argue that a classifier trained by a filtered dataset captures a more general knowledge model and should therefore perform better also on unseen cases. The proposed method is applied on a real-world software reliability analysis dataset and the obtained results are discussed.
Keywords: Data mining, Classification, Evolutionary decision trees, Filtering training sets, Software fault prediction, Search-based software engineering
EXTENSION of the file: .pdf
Special (Invited) Session: On Software Fault Prediction by Mining Software Complexity Data with Dynamically Filtered Training Sets
Organizer of the Session: 617-389
How Did you learn about congress: Peter Kokol (kokol@uni-mb.si), Luka Pavlic (luka.pavlic@gmail.com), Bostjan Grasic (bostjan.grasic@uni-mb.si)
IP ADDRESS: 164.8.251.158
