Support of semantics recovery during code scavenging using repository classification

One of the hardest tasks to be fulfilled during the analysis of legacy systems is how to determine the precise semantics of program components. Investigating the internal data and control structures is difficult due to the huge number of possible implementation variants for the same problem. To facilitate the task we propose to use components kept and described in a repository of reusable concepts as reference points. This becomes possible when behavior sampling is used as classification/retrieval strategy. In matching the results of isolated components from a legacy system against already executed components in a repository, one can tackle the problem of classifying legacy components without considering there internal structure. As a side effect, the population of the reuse repository is increased. In this paper we propose a model to reuse the knowledge containd in a behavior based reuse repository for analyzing, classifying and understanding isolated executable components from a legacy system. Components not yet classfied will augment the repository.