Large-scale software engineering requires communication and collaboration to successfully build and ship products. We conducted a survey with Microsoft engineers on inter-team coordination and found that the most impactful problems concerned finding and keeping track of other engineers. Since engineers are connected by their shared work, a tool that discovers connections in their work-related repositories can help. Here we describe the Codebook framework for mining software repositories. It is flexible enough to address all of the problems identified by our survey with a single data structure (graph of people and artifacts) and a single algorithm (regular language reachability). Codebook handles a larger variety of problems than prior work, analyzes more kinds of work artifacts, and can be customized by and for end-users. To evaluate our framework’s flexibility, we built two applications, Hoozizat and Deep Intellisense. We evaluated these applications with engineers to show effectiveness in addressing multiple inter-team coordination problems. Categories and Subject Descriptors:

Software teams often have trouble coordinating shared work due to poor communication practices. We surveyed software engineers (N=989) at Microsoft to investigate three rarely explored aspects of coordination: (1) how an engineer’s perception of dependence is predicted by his organizational characteristics, (2) how this perception differs when the dependence varies by the kinds of shared work artifacts, and (3) how the work group range affects the likelihood that an engineer will share information about work artifacts with another. Our results indicate that engineers tailor their communications about shared work for each group of intended recipients. This suggests that many existing coordination tools that rely on automatic mining and visualization of engineering activities have prevented senders from controlling the distribution of information about their work, and may have overestimated the receivers ’ abilities to comprehend it.

Development teams who work with others need to be aware of what everyone is doing in order to manage the risk of taking on dependencies. Using newsfeeds of software development activities mined from software repositories, teams can find relevant information to help them make well-informed decisions that affect the success of their endeavors. In this paper, we describe the architecture of a newsfeed system that we are currently building on top of the Codebook software repository mining platform. We discuss the design, construction and aggregation of newsfeeds, and include other important aspects such as summarization, filtering, context, and privacy. Categories and Subject Descriptors:

Social media has changed the way that people collaborate and share information. In this paper, we highlight its impact for enabling new ways for software teams to form and work together. Individuals will self-organize within and across organizational boundaries. Grassroots software development communities will emerge centered around new technologies, common processes and attractive target markets. Companies consisting of lone individuals will able to leverage social media to conceive of, design, develop, and deploy successful and profitable product lines. A challenge for researchers who are interested in studying, influencing, and supporting this shift in software teaming is to make sure that their research methods protect the privacy and reputation of their stakeholders.

Abstract—Large-scale software engineering requires many teams to collaborate together to create software products. The problems these teams suffer trying to coordinate their joint work can be addressed through tools inspired by social networking. Social networking tools help people to more easily discover and more efficiently maintain relationships than is feasible using one-to-one or face-to-face interactions. Applying these ideas to the software domain requires new kinds and combinations of software program and process analyses that overcome intrinsic limitations in the accuracy of the underlying data sources and the ambiguity inherent in human relationships. Keywords-software process, human aspects I.