Extracting concepts from file names: a new file clustering criterion
Proceedings of the 20th international conference on Software engineering
Intelligent Search Methods for Software Maintenance
Information Systems Frontiers
File clustering using naming conventions for legacy systems
CASCON '97 Proceedings of the 1997 conference of the Centre for Advanced Studies on Collaborative research
Intelligent search techniques for large software systems
CASCON '01 Proceedings of the 2001 conference of the Centre for Advanced Studies on Collaborative research
Applying data mining to software maintenance records
CASCON '03 Proceedings of the 2003 conference of the Centre for Advanced Studies on Collaborative research
Studying Software Engineers: Data Collection Techniques for Software Field Studies
Empirical Software Engineering
Empirical Software Engineering
Cross-artifact traceability using lightweight links
TEFSE '09 Proceedings of the 2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering
Semantic fault diagnosis: automatic natural-language fault descriptions
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
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Large, complex software systems are hard to learn and navigate. In an ideal environment, documentation can help in this process. However the latter is usually out of date and hard to use. Others have proposed using large knowledge bases to model software systems, however these are very expensive to build and may be as unmaintainable as the code. In this paper, we propose instead to use a highly circumscribed, small, conceptual knowledge base, whose purpose is to help the apprentice navigate a software system, and facilitate search within the code. We present our vision, and some initial experiments which involve building such a knowledge base in a semi-automated way.