Genetic improvement (GI) uses automated search to find improved versions of existing
software. We present a comprehensive survey of this nascent field of research with a focus …

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 …

In the last decade, machine-learning-based compilation has moved from an obscure
research niche to a mainstream activity. In this paper, we describe the relationship between …

Background Genetic studies are increasingly based on short noisy next generation
scanners. Typically complete DNA sequences are assembled by matching short NextGen …

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 …

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 …

Search Based Software Testing (SBST) formulates testing as an optimisation problem, which
can be attacked using computational search techniques from the field of Search Based …

Recent work on genetic-programming-based approaches to automatic program patching
have relied on the insight that the content of new code can often be assembled out of …

We show that the genetic improvement of programs (GIP) can scale by evolving increased
performance in a widely-used and highly complex 50000 line system. Genetic improvement …

Automated transplantation would open many exciting avenues for software development:
suppose we could autotransplant code from one system into another, entirely unrelated …