5 citations · 9 across the 4 of their papers we have counts for
4 papers
Mutation-Guided LLM-based Test Generation at Meta
Christopher Foster, Abhishek Gulati, Mark Harman +5
This paper describes Meta's ACH system for mutation-guided LLM-based test generation. ACH generates relatively few mutants (aka simulated faults), compared to traditional mutation…
Enhancing Testing at Meta with Rich-State Simulated Populations
Nadia Alshahwan, Arianna Blasi, Kinga Bojarczuk +11
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…
Automated Unit Test Improvement using Large Language Models at Meta
Nadia Alshahwan, Jubin Chheda, Anastasia Finegenova +6
This paper describes Meta's TestGen-LLM tool, which uses LLMs to automatically improve existing human-written tests. TestGen-LLM verifies that its generated test classes successful…
Assured LLM-Based Software Engineering
Nadia Alshahwan, Mark Harman, Inna Harper +3
In this paper we address the following question: How can we use Large Language Models (LLMs) to improve code independently of a human, while ensuring that the improved code - does…