One approach to supporting program comprehension involves binding concepts to source code. Previously proposed approaches to concept binding have enforced nonoverlapping boundaries. However, real-world programs may contain overlapping concepts. This paper presents techniques to allow boundary overlap in the binding of concepts to source code. In order to allow boundaries to overlap, the concept binding problem is reformulated as a search problem.

It is shown that the search space of overlapping concept bindings is exponentially large, indicating the suitability of sampling-based search algorithms. Hill climbing and genetic algorithms are introduced for sampling the space. The paper reports on experiments that apply these algorithms to 21 COBOL II programs taken from the commercial financial services sector. The results show that the genetic algorithm produces significantly better solutions than both the hill climber and random search.