Data-driven test selection at scale
Abstract
Large-scale services depend on Continuous Integration/Continuous Deployment (CI/CD) processes to maintain their agility and code-quality. Change-based testing plays an important role in finding bugs, but testing after every change is prohibitively expensive at a scale where thousands of changes are committed every hour. Test selection models deal with this issue by running a subset of tests for every change.
BibTeX
@inproceedings{Mehta-al:FSE21,
author = {Sonu Mehta and
Farima Farmahinifarahani and
Ranjita Bhagwan and
Suraj Guptha and
Sina Jafari and
Rahul Kumar and
Vaibhav Saini and
Anirudh Santhiar},
title = {Data-driven test selection at scale},
booktitle = {{ESEC/SIGSOFT} {FSE}},
pages = {1225--1235},
publisher = {{ACM}},
year = {2021},
}