Large language models for software engineering: A systematic literature review

X Hou, Y Zhao, Y Liu, Z Yang, K Wang, L Li… - ACM Transactions on …, 2024 - dl.acm.org
Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …

A systematic literature review on large language models for automated program repair

Q Zhang, C Fang, Y Xie, YX Ma, W Sun, Y Yang… - arXiv preprint arXiv …, 2024 - arxiv.org
Automated Program Repair (APR) attempts to patch software bugs and reduce manual
debugging efforts. Very recently, with the advances in Large Language Models (LLMs), an …

If llm is the wizard, then code is the wand: A survey on how code empowers large language models to serve as intelligent agents

K Yang, J Liu, J Wu, C Yang, YR Fung, S Li… - arXiv preprint arXiv …, 2024 - arxiv.org
The prominent large language models (LLMs) of today differ from past language models not
only in size, but also in the fact that they are trained on a combination of natural language …

Using gpt-4 turbo to automatically identify defeaters in assurance cases

KK Shahandashti, AB Belle… - 2024 IEEE 32nd …, 2024 - ieeexplore.ieee.org
Assurance cases (ACs) are convincing arguments, supported by a body of evidence and
aiming at demonstrating that a system will function as intended. Producers of systems can …

Do neutral prompts produce insecure code? formai-v2 dataset: Labelling vulnerabilities in code generated by large language models

N Tihanyi, T Bisztray, MA Ferrag, R Jain… - arXiv preprint arXiv …, 2024 - arxiv.org
This study provides a comparative analysis of state-of-the-art large language models
(LLMs), analyzing how likely they generate vulnerabilities when writing simple C programs …

Evaluating the Effectiveness of GPT-4 Turbo in Creating Defeaters for Assurance Cases

KK Shahandashti, M Sivakumar, MM Mohajer… - arXiv preprint arXiv …, 2024 - arxiv.org
Assurance cases (ACs) are structured arguments that support the verification of the correct
implementation of systems' non-functional requirements, such as safety and security …

How secure is AI-generated code: a large-scale comparison of large language models

N Tihanyi, T Bisztray, MA Ferrag, R Jain… - Empirical Software …, 2025 - Springer
This study compares state-of-the-art Large Language Models (LLMs) on their tendency to
generate vulnerabilities when writing C programs using a neutral zero-shot prompt. Tihanyi …

Large language models in source code static analysis

VN Ignatyev, NV Shimchik, DD Panov… - 2024 Ivannikov …, 2024 - ieeexplore.ieee.org
Applications of Large Language Models (LLM) for source code analysis and related tasks
arising during the development of an industrial static analyzer are becoming increasingly …

Tasks People Prompt: A Taxonomy of LLM Downstream Tasks in Software Verification and Falsification Approaches

VA Braberman, F Bonomo-Braberman… - arXiv preprint arXiv …, 2024 - arxiv.org
Prompting has become one of the main approaches to leverage emergent capabilities of
Large Language Models [Brown et al. NeurIPS 2020, Wei et al. TMLR 2022, Wei et al …

Assessing the Impact of GPT-4 Turbo in Generating Defeaters for Assurance Cases

K Khakzad Shahandashti, M Sivakumar… - Proceedings of the …, 2024 - dl.acm.org
Assurance cases (ACs) are structured arguments that allow verifying the correct
implementation of the created systems' non-functional requirements (eg, safety, security) …