
Large Language Models (LLMs) are very large deep learning models pre-trained on a vast amount of data. This article aims to provide an overview of the use of major language models in the field of software engineering from January 2021 to February 2024. It surveys the emerging area of Large Language Modeling in Software Engineering but acknowledges that to fully understand the issues, effects, and limitations of LLMs in this field, further research is needed. The article also highlights open research challenges for applying Large Language Models to technical problems faced by software engineers. The exceptional properties of LLMs bring novelty and creativity to applications within Software Engineering activities, including coding, design, requirements, repair, refactoring, performance improvement, documentation, and analytics. Our survey demonstrates the key role of reliable and efficient large language models in the development and deployment of Software Engineering.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
