Sapienz automated testing tool receives ISSTA 2026 Impact Paper Award
Meta's Sapienz testing infrastructure was recognized for its decade of impact in automated Android application testing.
Summary
Researchers Ke Mao, Mark Harman, and Yue Jia have been awarded the ISSTA 2026 Most Influential Paper Award for their 2016 research on Sapienz. Originally developed at University College London and later deployed at Meta, Sapienz uses multi-objective automated testing to find crashes and reduce reproduction steps. The tool now runs millions of daily tests across Meta's platforms and has expanded into areas like dynamic taint analysis at WhatsApp.
Technical capabilities of Sapienz
- Uses multi-objective exploration to maximize app coverage, increase crash detection, and minimize the steps required to trigger failures.
- Capable of performing dynamic taint analysis using test accounts with synthetic conversations.
- Scales to run millions of tests daily to support hundreds of monthly app releases.
- Principles are being extended to Large Language Model (LLM) agents for functional correctness and automated repair.
Why it matters
The recognition highlights the transition of academic research into large-scale industrial testing infrastructure used to secure major social platforms.
Original reference: engineering.fb.com →