Building Empirical Software Engineering Bodies of Knowledge with Systematic Knowledge Engineering

S. Biffl,M. Kalinowski, F. Ekaputra, E. Serral Asensio, D. Winkler:
"Building Empirical Software Engineering Bodies of Knowledge with Systematic Knowledge Engineering";
Vortrag: 26th International Conference on Software Engineering and Knowledge Engineering (SEKE 2014), Vancouver, Canada; 01.07.2014 - 02.07.2014; in:"Proceedings of the 26th International Conference on Software Engineering and Knowledge Engineering (SEKE)", Knowledge Systems Institute Graduate School, (2014), ISBN: 1-891706-35-7; S. 552 - 559.

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Abstract:


Abstract-[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 only to a limited
extent, which considerably slows down building BoKs incrementally.
[Objective] In this paper, we introduce the Systematic
Knowledge Engineering (SKE) process to support building up
BoKs from empirical studies efficiently. [Method] SKE is based on
the SLR process and on Knowledge Engineering (KE) practices to
provide a Knowledge Base (KB) with semantic technologies that
enable reusing intermediate data extraction results and querying
of empirical evidence. We evaluated SKE 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
in answering the queries, enabling knowledge reuse for analyses
beyond the results from the SLR process. [Conclusion] SKE
showed promising results in the software inspection context and
should be evaluated in other contexts for building EMSE BoKs
faster.