Large Language Models (LLMs), built upon Transformer-based architectures with massive
pretraining on diverse data, have not only revolutionized natural language processing but …

The emergence of the Internet of Things (IoT) introduced new classes of applications whose
latency and bandwidth requirements could not be satisfied by the traditional Cloud …

To support software developers in finding and fixing software bugs, several automated
program repair techniques have been introduced. Given a test suite, standard methods …

This paper provides a survey of the emerging area of Large Language Models (LLMs) for
Software Engineering (SE). It also sets out open research challenges for the application of …

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 …

Mutation testing realizes the idea of using artificial defects to support testing activities.
Mutation is typically used as a way to evaluate the adequacy of test suites, to guide the …

The use of Artificial Intelligence (ai), and more specifically of Deep Learning (dl), in modern
software systems, is nowadays widespread and continues to grow. At the same time, its …

Automated program repair is the problem of automatically fixing bugs in programs in order to
significantly reduce the debugging costs and improve the software quality. To address this …

This paper describes some of the challenges and opportunities when deploying static and
dynamic analysis at scale, drawing on the authors' experience with the Infer and Sapienz …

We report our experience with SapFix: the first deployment of automated end-to-end fault
fixing, from test case design through to deployed repairs in production code. We have used …