Mining Energy-Related Practices in Robotics Software

Abstract

Robots are becoming more and more commonplace in many industry settings. This successful adoption can be partly attributed to (1) their increasingly affordable cost and (2) the possibility of developing intelligent, software-driven robots. Unfortunately, robotics software consumes significant amounts of energy. Moreover, robots are often battery-driven, meaning that even a small energy improvement can help reduce its energy footprint and increase its autonomy and user experience.In this paper, we study the Robot Operating System (ROS) ecosystem, the de-facto standard for developing and prototyping robotics software. We analyze 527 energy-related data points (including commits, pull-requests and issues on ROS-related repositories, ROS-related questions on StackOverflow, ROS Discourse, ROS Answers and the official ROS Wiki).Our results include a quantification of the interest of roboticists on software energy efficiency, 10 recurrent causes and 14 solutions of energy-related issues, and their implied trade-offs with respect to other quality attributes. Those contributions support roboticists and researchers towards having energyefficient software in future robotics projects.1 We use the term data point as the superclass of any type of mined item, such as a commit message, a GitHub issue, or a discussion on StackOverflow.

Learning Software Project Management From Analyzing Q&A’s in the Stack Exchange

“…Due to the rich sources of valuable data, numerous studies have explored different Q&A communities such as Yahoo! Answers [6], Quora [7], Stack Overflow [8], [9], [10], and 1 https://pm.stackexchange.com/ [11] for different purposes. Such purposes include the identification of important conversations [12], uncovering the crucial factors that contribute to unanswered questions [13], addressing duplicate questions and quality issues [14], and designing an interactive approach for searching questions [15].…”