Observing the evolution of software systems at different levels of granularity has been a key issue for a number of studies, aiming at predicting defects or at studying certain phenomena, such as the presence of clones or of crosscutting concerns. Versioning systems such as CVS and SVN, however, only provide information about lines added or deleted by a contributor: any change is shown as a sequence of additions and deletions. This provides an erroneous estimate of the amount of code changed.

This paper shows how the evolution of changes at source code line level can be inferred from CVS repositories, by combining information retrieval techniques and the Levenshtein edit distance. The application of the proposed approach to the ArgoUML case study indicates a high precision and recall.