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As systems evolve their structure change in ways not expected upfront. As time goes by, the knowledge of the developers becomes more and more critical for the process of understanding the system. That is, when we want to understand a certain issue of the system we ask the knowledgeable developers. Yet, in large systems, not every developer is knowledgeable in all the details of the system. Thus, we would want to know which developer is knowledgeable in the issue at hand. In this paper we make use of the mapping between the changes and the author identifiers (e.g., user names) provided by versioning repositories. We first define a measurement for the notion of code ownership. We use this measurement to define the Ownership Map visualization to understand when and how different developers interacted in which way and in which part of the system 1 . We report the results we obtained on several large systems.

Understanding large software systems is a challenging task, and to support it many approaches have been developed. Often, the result of these approaches categorize existing entities into new groups or associates them with mutually exclusive properties. In this paper we present the Distribution Map as a generic technique to visualize and analyze this type of result. Our technique is based on the notion of focus, which shows whether a property is wellencapsulated or cross-cutting, and the notion of spread, which shows whether the property is present in several parts of the system. We present a basic visualization and complement it with measurements that quantify focus and spread. To validate our technique we show evidence of applying it on the result sets of different analysis approaches. As a conclusion we propose that the Distribution Map technique should belong to any reverse engineering toolkit.

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