5 papers · 1 filter
Pre-Training on Software Engineering Texts: Effects on Domain Adaptation and General-Language Understanding
Fabian C. Peña, Steffen Herbold
Generalist and code-focused Language Models (LMs) are increasingly applied to software engineering (SE), yet whether they are optimized for understanding SE textual artifacts (e.g.…
Large Language Models Have Unreliable Understanding of Software Engineering Terminology
Huzaifa Ejaz, Fabian C. Peña, Steffen Herbold
Large Language Models (LLMs) are increasingly used in software engineering (SE), yet there is no systematic study that determines to which degree these LLMs actually understand sta…
Utilizing LLMs for Industrial Process Automation: A Case Study on Modifying RAPID Programs
Salim Fares, Steffen Herbold
How to best use Large Language Models (LLMs) for software engineering is covered in many publications in recent years. However, most of this work focuses on widely-used general pur…
Evaluating the Performance and Efficiency of Sentence-BERT for Code Comment Classification
Fabian C. Peña, Steffen Herbold
This work evaluates Sentence-BERT for a multi-label code comment classification task seeking to maximize the classification performance while controlling efficiency constraints dur…
SELU: A Software Engineering Language Understanding Benchmark
Fabian C. Peña, Steffen Herbold
Large Language Models (LLMs) have demonstrated remarkable capabilities in code understanding and generation. However, their effectiveness on non-code Software Engineering (SE) task…