Alshahwan, Nadia;
Blasi, Arianna;
Bojarczuk, Kinga;
Ciancone, Andrea;
Gucevska, Natalija;
Harman, Mark;
Krolikowski, Michal;
... Lewis, Will; + view all
(2024)
Enhancing Testing at Meta with Rich-State Simulated Populations.
In:
Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice.
(pp. pp. 1-12).
ACM
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Abstract
This paper reports the results of the deployment of Rich-State Simulated Populations at Meta for both automated and manual testing. We use simulated users (aka test users) to mimic user interactions and acquire state in much the same way that real user accounts acquire state. For automated testing, we present empirical results from deployment on the Facebook, Messenger, and Instagram apps for iOS and Android Platforms. These apps consist of tens of millions of lines of code, communicating with hundreds of millions of lines of backend code, and are used by over 2 billion people every day. Our results reveal that rich state increases average code coverage by 38%, and endpoint coverage by 61%. More importantly, it also yields an average increase of 115% in the faults found by automated testing. The rich-state test user populations are also deployed in a (continually evolving) Test Universe; a web-enabled simulation platform for privacy-safe manual testing, which has been used by over 21,000 Meta engineers since its deployment in November 2022.
| Type: | Proceedings paper |
|---|---|
| Title: | Enhancing Testing at Meta with Rich-State Simulated Populations |
| Event: | ICSE-SEIP '24: 46th International Conference on Software Engineering: Software Engineering in Practice |
| Location: | PORTUGAL, Lisbon |
| Dates: | 14 Apr 2024 - 20 Apr 2024 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3639477.3639729 |
| Publisher version: | https://doi.org/10.1145/3639477.3639729 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Software Testing, Cyber Cyber Digital Twins, Simulation-Based Testing, Machine Learning |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10199776 |
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