Past studies show that developers who navigate code in a structural manner complete tasks faster and more correctly than those whose behavior is more opportunistic. The goal of this work is to move professional developers towards more effective program comprehension and maintenance habits by providing an approach that fosters structural code navigation. To this end, we created a Visual Studio plugin called Prodet that integrates an always-on navigable visualization of the most contextually relevant portions of the call graph. We evaluated the effectiveness of our approach by deploying it in a six week field study with professional software developers. The study results show a statistically significant increase in developers' use of structural navigation after installing Prodet. The results also show that developers continuously used the filtered and navigable call graph over the three week period in which it was deployed in production. These results indicate the maturity and value of our approach to increase developers' effectiveness in a practical and professional environment.

To complete a change task, software developers spend a substantial amount of time navigating code to understand the relevant parts. During this investigation phase, they implicitly build context models of the elements and relations that are relevant to the task. Through an exploratory study with twelve developers completing change tasks in three open source systems, we identified important characteristics of these context models and how they are created. In a second empirical analysis, we further examined our findings on data collected from eighty developers working on a variety of change tasks on open and closed source projects. Our studies uncovered, amongst other results, that code context models are highly connected, structurally and lexically, that developers start tasks using a combination of search and navigation and that code navigation varies substantially across developers. Based on these findings we identify and discuss design requirements to better support developers in the initial creation of code context models. We believe this work represents a substantial step in better understanding developers' code navigation and providing better tool support that will reduce time and effort needed for change tasks.