Concepts and Guidelines of Feature Modeling for Product Line Software Engineering

Author(s):  
Kwanwoo Lee ◽  
Kyo C. Kang ◽  
Jaejoon Lee
2009 ◽  
pp. 299-310
Author(s):  
Li Zheng ◽  
Chao Zhang ◽  
Zhanwei Wu ◽  
Yixin Yan

Author(s):  
Stefan Biffl ◽  
Marcos Kalinowski ◽  
Rick Rabiser ◽  
Fajar Ekaputra ◽  
Dietmar Winkler

Context. Software engineering researchers conduct systematic literature reviews (SLRs) to build bodies of knowledge (BoKs). Unfortunately, relevant knowledge collected in the SLR process is not publicly available, which considerably slows down building BoKs incrementally. Objective. We present and evaluate the Systematic Knowledge Engineering (SKE) process to support efficiently building BoKs from published research. Method. SKE is based on the SLR process and on Knowledge Engineering practices to build a Knowledge Base (KB) by reusing intermediate data extraction results from SLRs. We evaluated the feasibility of applying SKE by building a Software Inspection BoK KB from published experiments and a Software Product Line BoK KB from published experience reports. We compared the effort, benefits, and risks of building BoK KBs regarding the SKE and the traditional SLR processes. Results. The application of SKE for incrementally collecting and organizing knowledge in the context of a BoK was feasible for different domains and different types of evidence. While the efforts for conducting the SKE and traditional SLR processes are comparable, SKE provides significant benefits for building BoKs. Conclusions. SKE enables researchers in a scientific community to reuse and incrementally build knowledge in a BoK. SKE is ready to be evaluated in other software engineering domains.


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