Market introduction of automated driving features several motivations including road safety,
driving comfort, energy efficiency and totally new transport systems. However, many …

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 …

The main challenges are discussed together with the lessons learned from past and
ongoing research along the development cycle of machine learning systems. This will be …

A transcompiler, also known as source-to-source translator, is a system that converts source
code from a high-level programming language (such as C++ or Python) to another …

Recent advances in Deep Neural Networks (DNNs) have led to the development of DNN-
driven autonomous cars that, using sensors like camera, LiDAR, etc., can drive without any …

Among the many software testing techniques available today, fuzzing has remained highly
popular due to its conceptual simplicity, its low barrier to deployment, and its vast amount of …

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 …

Task automation has been greatly empowered by the recent advances in Large Language
Models (LLMs) via Python code, where the tasks ranging from software engineering …

A test oracle determines whether a test execution reveals a fault, often by comparing the
observed program output to the expected output. This is not always practical, for example …

Identifying invariants is an important program analysis task with applications towards
program understanding, bug finding, vulnerability analysis, and formal verification. Existing …