5 citations · 8 across the 4 of their papers we have counts for
5 papers
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…
Observation-based unit test generation at Meta
Nadia Alshahwan, Mark Harman, Alexandru Marginean +2
TestGen automatically generates unit tests, carved from serialized observations of complex objects, observed during app execution. We describe the development and deployment of Tes…
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…
Detecting Malware with Information Complexity
Nadia Alshahwan, Earl T. Barr, David Clark +1
This work focuses on a specific front of the malware detection arms-race, namely the detection of persistent, disk-resident malware. We exploit normalised compression distance (NCD…