Category:2014 - EMSE Body of Knowledge - Knowledge Base

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Duration: 06.2013 - ongoing


Short Description and Results

Paper Biffl, S., Kalinowski, M., Rabiser, R., Ekaputra, F. J., & Winkler, D. Systematic Knowledge Engineering: Building Bodies of Knowledge from Published Research. International Journal of Software Engineering and Knowledge Engineering, Vol. 24, No. 10, pp. 1533-1571, 2014 (SEKE 2014 Best Papers).

[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.


Paper Biffl, S., Kalinowski, M., Ekaputra, F. J., Serral, E., & Winkler, D. (July 2014). Building Empirical Software Engineering Bodies of Knowledge with Systematic Knowledge Engineering. International Conference on Software Engineering and Knowledge Engineering (SEKE), pp. 552-559, Vancouver, Canada, 2014.

[Context] Empirical software engineering (EMSE) researchers conduct systematic literature reviews (SLRs) to build bodies of knowledge (BoKs). Unfortunately, valuable knowledge collected in the SLR process is publicly available in research syntheses reports only to a limited extent, which considerably slows down building BoKs incrementally. [Objective] In this paper, we introduce the Systematic Knowledge Engineering (SKE) approach to support building up EMSE BoKs from empirical studies efficiently. [Method] SKE extends the SLR process and provides a Knowledge Base (KB) toreuse intermediate data extraction results in future research analyses. We evaluated the SKE approach by building a software inspection EMSE BoK KB from knowledge acquired by controlled experiments. We elicited relevant queries from EMSE researchers and systematically integrated information from 30 representative research papers into the KB. [Results] The resulting KB was effective and efficient in answering the relevant queries, enabling knowledge reuse for analyses beyond the results from the SLR process. [Conclusion] The SKE approach showed promising results in the software inspection context and should be also evaluated in other contexts for building EMSE BoKs faster.


[Link to preliminary technical report http://qse.ifs.tuwien.ac.at/publication/IFS-CDL-13-03.pdf]


Pages in category "2014 - EMSE Body of Knowledge - Knowledge Base"

The following 3 pages are in this category, out of 3 total.

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