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CBR for Experimental Software Engineering



Lenz, M.; Bartsch-Spörl, B.; Burkhard, H.-D.; Wess, S.:
Case-Based Reasoning Technology. From Foundations to Applications
Berlin: Springer, 1998 (Lecture Notes in Artificial Intelligence 1400)
ISBN: 3-540-64572-1
ISSN: 0302-9743
pp.235-254 : Ill.
Book Article
Fraunhofer IESE ()
case-based reasoning; experience base implementation; experience factory; experimental software engineering

Objective of our work is to exploit the mutual interrelations between case-based reasoning (CBR) and experimental software engineering (ESE) for the sake of both fields. In particular, we address the following topics: - Present a logical infrastructure of organizational learning in the software domain that makes use of principles, methods, and established practices from CBR. -Utilize CBR technology for implementing experience bases. - Transfer the augmented infrastructure for organizational learning from experimental software engineering to other application fields such as mechanical engineering. - Outline additional uses of CBR for ESE that go beyond infrastructures for organizational learning (i.e., data analysis, problem solving, etc.). - Evolve the methodology for developing CBR-based software systems based on software engineering methods and practices that are established in other application domains. These topics are gradually developed throughout this chapter. We start with b ri ef introductions to software engineering and ESE (sections 2 and 3). Then, we outline possible CBR support for ESE and give an overview on research related to both CBR and ESE (sections 4 and 5). In the major part of this chapter we describe the approach we take at the Fraunhofer Institute for Experimental Software Engineering in Kaiserslautern (section 6). Besides this description we also report on two case studies and give an outlook on work still to be done (sections 7 and 8).