2nd International Workshop on Knowledge-Oriented Product Line Engineering: KOPLE 2011

Venue: Munich, Germany. Held in conjunction with the 15th International Software Product Line Conference (SPLC 2011) August 22 to 26, 2011
Date: 2011.08.26
Duration: 1 day
Organiser: SECC, SAP, European Software Institute - TECNALIA

Download Call for Papers

Submissions deadline extended: Monday, June 13

Software Product Line Engineering (PLE) exploits systematic reuse by identifying and methodically reusing software artifacts to develop different but related software systems.

Developing Product Lines requires analysis skills to identify, model, and encode domain and product knowledge into artifacts that can be systematically reused across the development life-cycle. As such, Knowledge plays a paramount role in the success of the various activities of PLE.

The objective of KOPLE is to bring together SPL researchers and practitioners from academia and industry to investigate the role of Knowledge in PLE. Knowledge is usually encapsulated in PL architectures in a tacit or implicit way, and this may appears to be sufficient for industry to implement successful product lines. Nevertheless, KOPLE also aims to become a discussion forum about techniques and methods to convert from tacit to explicit Knowledge in PLE and to process and use this Knowledge for optimizing and innovating PLE processes.

The key specific objectives of the KOPLE workshop can be summarized as follows:

• Compile current practices and experience in applying knowledge engineering techniques in engineering product line architectures
• Explore and discuss how the PLE industry can benefit from the knowledge engineering community and vice versa
• Discuss and document challenges and barriers for knowledge management and modeling in PLE
• Investigate various innovative techniques for modeling, developing, and implementing knowledge-oriented PLE
• Initiate a Working Group that focuses on knowledge issues related to PLE to further develop this area and its practice

KOPLE 2011 WORKSHOP PROGRAM

KEYNOTE INFORMATION

Knowledge Capture and Reasoning for Software Product Lines

Knowledge-oriented and model-driven engineering of Software Product Lines (SPLs) are both about modeling the commonalities and variabilities of the systems in the SPL and sharing these models among the SPL's stakeholders. This talk will start with successful examples of variability models from open source ecosystems, which capture mostly binary configuration options, and it will progress to structurally richer models, illustrated using the Clafer language. I will connect these richer models to ontology engineering, language engineering, behavioral models, and reasoning technologies. I will discuss the prospects of such models being successful in practice and the challenges that need to be addressed.
 

Krzysztof Czarnecki is Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo and NSERC/Bank of Nova Scotia Industrial Research Chair in Requirements Engineering of Service-oriented Software Systems. He received the MS degree in Computer Science from California State University, Sacramento, and his PhD in Computer Science from Technical University of Ilmenau, Germany. Before coming to University of Waterloo in 2003, he worked for eight years at DaimlerChrysler Research, Germany, focusing on improving software development practices and technologies in enterprise and embedded domains. He is a co-author of the book "Generative Programming" (Addison- Wesley, 2000). He received the Premier's Research Excellence Award in 2004 and the British Computing Society in Upper Canada Award for Outstanding Contributions to IT Industry in 2008. He is the Principal Investigator of a $9.3 million project on "Model-Based Software Service Engineering", funded by the Province of Ontario (2008-2013). His work focuses on developing model-based approaches to software engineering that work in industrial practice.

Workshop topics

Knowledge-based domain modeling

• Domain analysis and Knowledge Engineering
• Knowledge representation in PL
• Extending existing variability languages with (more) semantics
• Ontologies in PLE
• Conceptual graphs in PLE
• Experts systems in PLE
• Domain-Specific Knowledge-Oriented PL
• Metrics for Knowledge-Oriented PL

Exploiting knowledge-based Product Lines

• Tool support for Knowledge-Oriented PL
• Context-based variability resolution
• Business decision-making support
• Life-cycle evolution and optimization
• Methodologies and processes supporting Knowledge-Oriented PL exploitation
• Organizational issues and knowledge management in PLE
• Economical/value aspects of adopting Knowledge-Oriented PLE
• Testing PL architectures and Knowledge Engineering
• Knowledge management of PL architecture evolution
• PL architecture scoping and Knowledge Engineering

 Mining knowledge in Product Line Engineering 

• Knowledge acquisition and elicitation in PL.
• Techniques for the inference of knowledge from PL assets
• Techniques for the extraction of knowledge from products for PL adoption/discovery
• Reasoning techniques for PLE
• Artificial-Intelligence techniques applied to PLE
• Usage of discovered knowledge

Practical experience in developing Knowledge-Oriented PL

• Domain analysis and Knowledge Engineering in specific domains
• Industry case studies
• Experience reports