Large language models for software engineering: A systematic literature review
Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …
Software Engineering (SE). Many recent publications have explored LLMs applied to …
Software testing with large language models: Survey, landscape, and vision
Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …
technology in natural language processing and artificial intelligence, with the ability to …
Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models
Recent advances in Large Language Models (LLM) have made automatic code generation
possible for real-world programming tasks in general-purpose programming languages …
possible for real-world programming tasks in general-purpose programming languages …
Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation
Pre-trained models for Natural Languages (NL) like BERT and GPT have been recently
shown to transfer well to Programming Languages (PL) and largely benefit a broad set of …
shown to transfer well to Programming Languages (PL) and largely benefit a broad set of …
Program synthesis with large language models
This paper explores the limits of the current generation of large language models for
program synthesis in general purpose programming languages. We evaluate a collection of …
program synthesis in general purpose programming languages. We evaluate a collection of …
An empirical evaluation of using large language models for automated unit test generation
Unit tests play a key role in ensuring the correctness of software. However, manually
creating unit tests is a laborious task, motivating the need for automation. Large Language …
creating unit tests is a laborious task, motivating the need for automation. Large Language …
Large language models meet nl2code: A survey
The task of generating code from a natural language description, or NL2Code, is considered
a pressing and significant challenge in code intelligence. Thanks to the rapid development …
a pressing and significant challenge in code intelligence. Thanks to the rapid development …
Retrieval-based prompt selection for code-related few-shot learning
Large language models trained on massive code corpora can generalize to new tasks
without the need for task-specific fine-tuning. In few-shot learning, these models take as …
without the need for task-specific fine-tuning. In few-shot learning, these models take as …
Towards an understanding of large language models in software engineering tasks
Abstract Large Language Models (LLMs) have drawn widespread attention and research
due to their astounding performance in text generation and reasoning tasks. Derivative …
due to their astounding performance in text generation and reasoning tasks. Derivative …
No more fine-tuning? an experimental evaluation of prompt tuning in code intelligence
Pre-trained models have been shown effective in many code intelligence tasks. These
models are pre-trained on large-scale unlabeled corpus and then fine-tuned in downstream …
models are pre-trained on large-scale unlabeled corpus and then fine-tuned in downstream …