How Developers Drive Software Evolution

Abstract

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.

A degree-of-knowledge model to capture source code familiarity

“…The Emergent Expertise Locator refines the approach of the Expertise Browser by considering the relationship between files that were changed together when determining expertise [10]. Girba and colleagues consider finer-grained information, equating expertise with the number of lines of code each developer changes [4]. Hattori and colleagues consider changes that have not yet been committed [5].…”

Dynamic Analysis of Communication and Collaboration in OSS Projects

“…This enables the analysis of the interaction between the developer and the owner of a file, and, in particular, how the communication between the two proceeds. Girba et al propose a measurement for the notion of code ownership by evaluating the CVS log [10]. They define the owner of a source file as being the developer that contributed the most code lines to it.…”

On porting software visualization tools to the web

“…Wu et al [61] used the spectograph metaphor to visualize how changes occur in software systems. The Ownership Map [23], introduced by Gîrba et al visualizes code ownership of files over time, based on information extracted from CVS logs. The Evolution Radar visualizes co-change information extracted from SCM logs, integrating different levels of abstraction, to support the analysis of the coupling at the module level and the understanding of the causes at the file level [10].…”