Session organizers: Peter Kokol and Vili Podgorelec, University of Maribor, Slovenia

SCOPE AND CALL FOR PAPERS

Among many possible solutions in still persisting software crisis is the "hidden knowledge" in large software projects databases. The conventional statistical approaches can usually not explore and encounter this knowledge, thereafter intelligent system and data mining are viable candidates to replace or complement them. But there are a lot of problems even with conventional intelligent systems and data mining techniques in conventional applications. Thereafter the session will focus on novel approaches (i.e. novel ways of integrating neural networks, rough sets, evolutionary programming, agent technologies, decision trees, etc), new intelligent system and data mining design methodologies and tools specially suited to encounter new software engineering knowledge or even rules and laws. Additional aim is to solve some of the hard intelligent systems/data mining problems like ortogonality, reducing the number of iterations needed for near-optimal solutions (using the chaos theory) and the problem of noisy and incomplete data.

This session considers all aspects of using computational intelligence, soft computing techniques and intelligent systems (IS) for data mining (DM), analysing and discovering patterns, rules and/or knowledge in software projects databases and software data. We invite papers that address theoretical foundations, practical techniques, software tools, applications and/or experience reports in the area. The following is a non-exhaustive list of topics of special interest to this technical session:

Chaos theory, science of complexity
Data mining and knowledge discovery in software engineering
Intelligent software data analysis
Measurements and software metrics based on software projects data
Novel ways of integrating neural networks, rough sets, evolutionary programming, agent technologies, decision trees
New IS and DM design methodologies and tools specially suited to encounter new software engineering knowledge
Empirical studies, experience, and lessons learned on mining software projects data
Solutions to hard IS/DM problems like ortogonality, reducing the number of iterations needed for near-optimal solutions (using the chaos theory) and the problem of noisy and incomplete data

PAPER SUBMISSION AND PUBLICATION

Submitted papers have to be original, containing new and original results. The papers are to be formatted according to the author's instructions found at the following link (format files): Microsoft Word Template; the length should not exceed 6 pages. Please send the full paper (in PDF or Word format) as an email attachment to Vili Podgorelec at the latest on July 11, 2004.

Submission implies the willingness of at least one of the authors to register and present the paper at the SEA 2004 conference. All papers will be peer reviewed by at least two independent referees. All accepted papers will be included in the conference proceedings and published by IASTED. Additionally, the substantially extended versions of the accepted papers in this session might be considered for the special issue of an international software engineering journal, depending on the quality of submitted papers.

IMPORTANT DATES

Paper submission due (full paper): July 11, 2004.
Notification of acceptance: August 20, 2004.
Camera ready papers and authors' registration : September 7, 2004.
SEA 2004 conference at MIT Cambridge, MA, USA: November 9-11, 2004.

For any additional information regarding location, registration, accomodation, etc. please consult the SEA 2004 webpage.

CONTACTS

Peter Kokol, kokol@uni-mb.si
Vili Podgorelec, vili.podgorelec@uni-mb.si