Normalizing source code vocabulary to support program comprehension and software quality
Proceedings of the 2013 International Conference on Software Engineering
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Understanding source code identifiers, by identifying words composing them, is a necessary step for many program comprehension, reverse engineering, or redocumentation tasks. To this aim, researchers have proposed several identifier splitting and expansion approaches such as Samurai, TIDIER and more recently GenTest. The ultimate goal of such approaches is to help disambiguating conceptual information encoded in compound (or abbreviated) identifiers. This paper presents TRIS, TRee-based Identifier Splitter, a two-phases approach to split and expand program identifiers. First, TRIS pre-compiles transformed dictionary words into a tree representation, associating a cost to each transformation. In a second phase, it maps the identifier splitting/expansion problem into a minimization problem, i.e., the search of the shortest path (optimal split/expansion) in a weighted graph. We apply TRIS to a sample of 974 identifiers extracted from JHotDraw, 3,085 from Lynx, and to a sample of 489 identifiers extracted from 340 C programs. Also, we compare TRIS with GenTest on a set of 2,663 mixed Java, C and C++ identifiers. We report evidence that TRIS split (and expansion) is more accurate than state-of-the-art approaches and that it is also efficient in terms of computation time.