Visualizing feature evolution of large-scale software based on problem and modification report data

Gaining higher level evolutionary information about large software systems is a key challenge in dealing with increasing complexity and architectural deterioration. Modification reports and problem reports taken from systems such as CVS and Bugzilla contain an overwhelming amount of information about the reasons and effects of particular changes. Such reports can be analyzed to provide a clearer picture about the problems concerning a particular feature or a set of features. Hidden dependencies of structurally unrelated but over time logically coupled files exhibit a high potential to illustrate feature evolution and possible architectural deterioration. In this paper, we describe the visualization of feature evolution by taking advantage of this logical coupling introduced by changes required to fix a reported problem. We compute the proximity of problem reports by applying a standard technique called Multidimensional Scaling (MDS). The visualization of these data enables to depict feature evolution by projecting problem report dependence onto (a) feature-connected files and (b) onto the project directory structure of the software system. These two different views show how problem reports, features and directory tree structure relate. As a result, our approach uncovers hidden dependencies between features and presents them in easy-to-assess visual form. A visualization of interwoven features can indicate locations of design erosion in the architectural evolution of a software system. As a case study, we used Mozilla and its CVS and Bugzilla data to show th