Large language models for software engineering: A systematic literature review

X Hou, Y Zhao, Y Liu, Z Yang, K Wang, L Li… - arXiv preprint arXiv …, 2023 - arxiv.org
Large Language Models (LLMs) have significantly impacted numerous domains, notably
including Software Engineering (SE). Nevertheless, a well-rounded understanding of the …

Programming languages and compiler design for realistic quantum hardware

FT Chong, D Franklin, M Martonosi - Nature, 2017 - nature.com
Quantum computing sits at an important inflection point. For years, high-level algorithms for
quantum computers have shown considerable promise, and recent advances in quantum …

Faster sorting algorithms discovered using deep reinforcement learning

DJ Mankowitz, A Michi, A Zhernov, M Gelmi, M Selvi… - Nature, 2023 - nature.com
Fundamental algorithms such as sorting or hashing are used trillions of times on any given
day. As demand for computation grows, it has become critical for these algorithms to be as …

Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models

P Vaithilingam, T Zhang, EL Glassman - Chi conference on human …, 2022 - dl.acm.org
Recent advances in Large Language Models (LLM) have made automatic code generation
possible for real-world programming tasks in general-purpose programming languages …

cvc5: A versatile and industrial-strength SMT solver

H Barbosa, C Barrett, M Brain, G Kremer… - … Conference on Tools …, 2022 - Springer
Abstract cvc5 is the latest SMT solver in the cooperating validity checker series and builds
on the successful code base of CVC4. This paper serves as a comprehensive system …

Github copilot ai pair programmer: Asset or liability?

AM Dakhel, V Majdinasab, A Nikanjam… - Journal of Systems and …, 2023 - Elsevier
Automatic program synthesis is a long-lasting dream in software engineering. Recently, a
promising Deep Learning (DL) based solution, called Copilot, has been proposed by …

Program synthesis with large language models

J Austin, A Odena, M Nye, M Bosma… - arXiv preprint arXiv …, 2021 - arxiv.org
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 …

MultiPL-E: a scalable and polyglot approach to benchmarking neural code generation

F Cassano, J Gouwar, D Nguyen… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Large language models have demonstrated the ability to generate both natural language
and programming language text. Although contemporary code generation models are …

Generalized planning in pddl domains with pretrained large language models

T Silver, S Dan, K Srinivas, JB Tenenbaum… - Proceedings of the …, 2024 - ojs.aaai.org
Recent work has considered whether large language models (LLMs) can function as
planners: given a task, generate a plan. We investigate whether LLMs can serve as …

Large language models are few-shot testers: Exploring llm-based general bug reproduction

S Kang, J Yoon, S Yoo - 2023 IEEE/ACM 45th International …, 2023 - ieeexplore.ieee.org
Many automated test generation techniques have been developed to aid developers with
writing tests. To facilitate full automation, most existing techniques aim to either increase …