Detection and analysis of similar code fragments (“code clones”) has become an integral part of software maintenance. In response, over the last decade a great many clone detection techniques and tools have been proposed. However, identifying useful cloning information from the large volume of textual data produced by these detectors is challenging. VisCad is a tool with which a user can visualize and analyze large volumes of raw cloning data in an interactive fashion. Users can analyze and identify distinctive code clones through a set of visualization techniques, metrics and data filtering operations. The loosely coupled architecture of VisCad allows users to work with the clones of any clone detection tools that report source co-ordinates of the found clones. This yields the opportunity to work with the clone detectors of choice, which is important for clone analysis since clone detectors have their own strengths and weaknesses.