Adapting Bug Prediction Models to Predict Reverted Commits at Wayfair
Researchers have proposed many algorithms to predict software bugs. Given a software entity (e.g., a file or method), these algorithms predict whether the entity is bug-prone. However, since these algorithms cannot identify \textit{specific} bugs, this does not tend to be particularly useful in practice. In this work, we adapt this prior work to the related problem of predicting whether a commit is likely to be reverted. Given the batch nature of continuous integration deployment at scale, this allows developers to find time-sensitive bugs in production more quickly. The models in this paper are based on features extracted from the revision history of a codebase that are typically used in bug prediction. Our experiments, performed on the three main repositories for the Wayfair website, show that our models can rank reverted commits above 80% of non-reverted commits on average. Moreover, when given to Wayfair developers, our models reduce the amount of time needed to find certain kinds of bugs by 55%. Wayfair continues to use our findings and models today to help find bugs during software deployments.
Co-founder of Parsagon.io; former machine learning researcher for Wayfair Research
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 | ||
