Hard Cases in Source Code to Architecture Mapping using Naive Bayes

• The automatic mapping of source code entities to architectural modules is a challenging problem that is necessary to solve if we want to increase the use of Static Architecture Conformance Checking in the industry. We apply the state-of-the-art automatic mapping technique to eight open-source systems and find that there are systematic problems in the automatically created mappings. All of these eight systems have small modules that are very hard to map correctly since only a few source code entities are mapped to these. All systems seem to use some naming strategy, mapping source code to modules; however, naming is often ambiguous. We also find differences in ground truth mappings performed by experts, which affect mappings based on these, and that architectural refactoring also affects the mapping performance. 

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)

Keyword

Incremental clustering

Orphan adoption

Naive Bayes

Software architecture

Machine learning

Computer Science

Datavetenskap

Publication and Content Type

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kon (subject category)