| dc.description.abstract | During software development, design rules and contracts
in the source code are often encoded through regularities,
such as API usage protocols, coding idioms and naming conventions.
The structural regularities that govern a program can
aid in comprehension and maintenance of the application, but
are often implicit or undocumented. Tool support for extracting
these regularities from the source code can provide developers
useful insights. But building such tool support is not trivial, in
particular, because the informal nature of regularities results in
frequent deviations and exceptions to these regularities.
We propose an automated approach, based on association rule
mining, to discover the structural regularities that govern the
source code of a software system.We chose this technique because
of its resilience to exceptions. In general, tool support for mining
regularities tends to discover a huge amount of rules, making
interpretation of the results hard and time-consuming. To ease
the interpretation, we reduce the results to a minimal canonical
form, and group them to obtain a more rational description of
the discovered regularities. As an initial feasibility study of our
approach, we applied it on two open-source systems, namely
IntensiVE (Smalltalk) and FreeCol (Java). | en_US |
