Machine Learning with Value-Based Software Engineering
Hotel Sofitel. San Francisco Bay, USA , July 1– July 3, 2010
special session in
The Twenty-Second International Conference on Software Engineering and Knowledge Engineering
Organized by Knowledge Systems Institute, U.S.A.
Software engineering research and practice thus far are mainly conducted in a value-neutral setting where each artifact in software development such as a requirement, a use case, a test case, a defect, and so forth, is treated as equally important during a software system development process. There are a number of shortcomings of such value-neutral software engineering. Value-based software engineering (VBSE) is to integrate value considerations into the full range of existing and emerging software engineering principles and practices so as to increase the return on investment for the stakeholders and optimize other relevant value objectives of software projects.
Machine learning (ML) has been playing an increasingly important role in helping develop and maintain large and complex software systems. However, machine learning applications to software engineering have been largely confined to the value-neutral software engineering setting. In this special session, the main theme to be emphasized is that there is great potential to apply ML methods to VBSE. The training data or the background knowledge or domain theory or heuristics or bias used by ML methods in generating target models or functions for software development and maintenance should be aligned with stakeholders' value propositions (SVPs) and business objectives.
This special session will focus on the current research topics in applying ML to VBSE. Pertinent topics include, but are not limited to:
- Value-based requirements engineering
- Value-based architecturing
- Value-based design and development
- Value-based verification and validation
- Value-based testing
- Value-based planning and control
- Value-based maintenance
- Value-based risk management
- Value-based quality management
- Value-based people management
- Value-based software Cost and Effort Estimation
- Value-based software metrics
- Case studies of ML application in VBSE
- Guidelines and heuristics in aligning SVP with ML methods
SUBMISSION OF PAPERS
Submitted papers must not be previously published or be under consideration for publication elsewhere. Authors must follow the submission guidelines of SEKE 2010. When submitting your papers to the session, please select "Special Session: Machine Learning with Value-based Software Engineering - Zhang" in the pull-down menu for paper type (http://conf.ksi.edu/seke2010/submit/SubmitPaper.php).
In addition to submitting papers to the conference web site, authors are asked to email a copy of their paper(s) to Du Zhang on or before the submission deadline.
All accepted papers for this special session will be published in the proceedings of SEKE 2010. A selection of presented papers in the session will be considered for inclusion, after revision, in a special issue of either the International journal of Software Engineering and Knowledge Engineering (http://www.worldscinet.com/ijseke/ijseke.shtml), or the International Journal of Software Science and Computational Intelligence (http://www.igi-global.com/journals/details.asp?ID=7981).
- Paper submission due: March 22, 2010 (Firm)
- Notification of acceptance: April, 20, 2010
- Camera-ready copy: May 10, 2010
- Workshop and conference date: July 1-3, 2010
Dept. of Computer Science
California State University
6000 J Street
Sacramento, CA 95819-6021
Tel: (916) 278-7628
Fax: (916) 278-6774