Large Language Models (LLMs) have demonstrated remarkable performance in code
completion. However, due to the lack of domain-specific knowledge, they may not be optimal …

In software engineering, a great number of new approaches are being actively researched,
and a lot of tools are being developed based on them. These tools require a framework for …

Machine learning techniques for cybersecurity-related software engineering tasks are
becoming increasingly popular. The representation of source code is a key portion of the …

As researchers and practitioners apply Machine Learning to increasingly more software
engineering problems, the approaches they use become more sophisticated. A lot of …

Method name prediction (MNP) aims to recommend a proper name for a method given by
the developer, which can ease the programming task and improve programmer productivity …

Code search aims to search for code snippets from large codebase that are semantically
related to natural query statements. Deep learning is a valuable method for solving code …

Teaming is a key aspect of most professional software engineering positions, and
consequently, team-based learning (TBL) features heavily in many undergraduate computer …

Annotations add metadata to source code entities such as classes or functions, which later
can be processed by so-called annotation processors to, for example, modify the annotated …

Analyzing and evaluating student-generated code poses a big headache for programming
education. Code evaluation is a delicate task requiring accuracy, efficiency, and error …

In software development, system integrity is a measure of the impact code changes have on
them. It is determined by the team's comprehension. However, rapid evolution of change …