Software engineers generate vast quantities of development artifacts such as source code, defect data, commit history, test suits, usage logs, documentation, etc., as they create and maintain their projects. The information contained in these artifacts could provide valuable insights into the software projects (e.g., software quality, development productivity, or user experience). However, extracting meaningful facts and interpreting them is not feasible just by looking at the raw data; thus, stakeholders often make daily decisions based on their intuition or previous experience.

In this talk, I will demonstrate how data analytics can be used to leverage large volumes of data and provide practitioners with up-to-date and insightful information that can support informed decisions around software projects. In particular, I will talk about employing analytics to help developers gain and maintain ongoing awareness on their projects and activities, and support their day-to-day development tasks such as resolving issues, submitting a patch for a review, and conducting code reviews.