Software development is a data rich activity with many sophisticated metrics. Yet engineers often lack the tools and techniques necessary to leverage these potentially powerful information resources toward decision making. In this paper, we present the data and analysis needs of professional software engineers. The survey responses lead us to propose several guidelines for analytics tools in softw
are development including: Engineers do not necessarily have much expertise in data analysis; thus tools should be easy to use, fast, and produce concise output. Engineers have diverse analysis needs and consider most indicators to be important; thus tools should at the same time support many different types of artifacts and many indicators. In addition, engineers want to drill down into data based on time, organizational structure, and system architecture. We validated our guidelines with a proof-of-concept implementation of an analytics tool, which we used to solicit additional feedback from engineers on how future analytics tools should be designed.
