This paper introduces BEE, a tool that automatically analyzes user-written bug reports and provides feedback to reporters and developers about the system's observed behavior (OB), expected behavior (EB), and the steps to reproduce the bug (S2R). BEE employs machine learning to (i) detect if an issue describes a bug, an enhancement, or a question; (ii) identify the structure of bug descriptions by automatically labeling the sentences that correspond to the OB, EB, or S2R; and (iii) detect when bug reports fail to provide these elements. BEE is integrated with GitHub and offers a public web API that researchers can use to investigate bug management tasks based on bug reports. We evaluated BEE's underlying models on more than 5k existing bug reports and found they can correctly detect OB, EB, and S2R sentences as well as missing information in bug reports. BEE is an open-source project that can be found at \url{https://git.io/JfFnN}. A screencast showing the full capabilities of BEE can be found at \url{https://youtu.be/8pC48f_hClw}.
Wed 11 NovDisplayed time zone: (UTC) Coordinated Universal Time change
01:00 - 01:30 | Developer Support 2Research Papers / Tool Demos / Industry Papers / Paper Presentations / Visions and Reflections at Virtual room 1 | ||
01:00 2mTalk | Adapting Bug Prediction Models to Predict Reverted Commits at Wayfair Industry Papers Alexander Suh Wayfair Research, USA DOI | ||
01:03 1mTalk | ARCADE: An Extensible Workbench for Architecture Recovery, Change, and Decay Evaluation Tool Demos Marcelo Schmitt Laser University of Southern California, USA, Nenad Medvidović University of Southern California, USA, Duc Minh Le Bloomberg, USA, Joshua Garcia University of California, Irvine DOI | ||
01:05 1mTalk | BEE: A Tool for Structuring and Analyzing Bug Reports Tool Demos DOI | ||
01:07 1mTalk | Enhancing Developers' Support on Pull Requests Activities with Software Bots Paper Presentations Mairieli Wessel University of São Paulo | ||
01:09 1mTalk | Heard It through the Gitvine: An Empirical Study of Tool Diffusion across the npm Ecosystem Research Papers Hemank Lamba Carnegie Mellon University, USA, Asher Trockman Carnegie Mellon University, USA, Daniel Armanios Carnegie Mellon University, USA, Christian Kästner Carnegie Mellon University, USA, Heather Miller Carnegie Mellon University, USA, Bogdan Vasilescu Carnegie Mellon University, USA DOI | ||
01:11 1mTalk | Next Generation Automated Software Evolution Refactoring at Scale Visions and Reflections James Ivers Carnegie Mellon University, USA, Ipek Ozkaya Carnegie Mellon Software Engineering Institute, Robert Nord Software Engineering Institute, Chris Seifried Carnegie Mellon University, USA DOI | ||
01:13 17mTalk | Conversations on Developer Support 2 Paper Presentations Alexander Suh Wayfair Research, USA, Ipek Ozkaya Carnegie Mellon Software Engineering Institute, Mairieli Wessel University of São Paulo, Marcelo Schmitt Laser University of Southern California, USA, Yang Song University of North Carolina Wilmington, M: Bonita Sharif University of Nebraska-Lincoln, USA | ||