Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …

The recent success of large language models (LLMs) trained on static, pre-collected,
general datasets has sparked numerous research directions and applications. One such …

Large language models (LLMs) demonstrate impressive capabilities to generate accurate
code snippets given natural language intents in a zero-shot manner, ie, without the need for …

Software Engineering (SE) is the systematic design, development, maintenance, and
management of software applications underpinning the digital infrastructure of our modern …

For decades, much software engineering research has been dedicated to devising
automated solutions aimed at enhancing developer productivity and elevating software …

[Context] Large Language Models (LLMs) have shown good performance in several
software development-related tasks such as program repair, documentation, code …

Incremental learning is the ability of systems to acquire knowledge over time, enabling their
adaptation and generalization to novel tasks. It is a critical ability for intelligent, real-world …

The rapid evolution of software libraries presents a significant challenge for code generation
models, which must adapt to frequent version updates while maintaining compatibility with …

Code review is a crucial process before deploying code to production, as it validates the
code, provides suggestions for improvements, and identifies errors such as missed edge …

Motivated by recent work on lifelong learning applications for language models (LMs) of
code, we introduce CodeLL, a lifelong learning dataset focused on code changes. Our …