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20212025
most citedFully Autonomous Programming with Large Language Models

43 citations · 73 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.SE2025★ 1 cited

The Impact of Fine-tuning Large Language Models on Automated Program Repair

Roman Macháček, Anastasiia Grishina, Max Hort +1

Automated Program Repair (APR) uses various tools and techniques to help developers achieve functional and error-free code faster. In recent years, Large Language Models (LLMs) hav…

cs.SE2024

Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation

Fernando Vallecillos Ruiz, Anastasiia Grishina, Max Hort +1

Research shows that errors in natural language can be corrected by translating texts to another language and back using language models. We explore to what extent this latent corre…

cs.SE2023★ 2 cited

An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code

Max Hort, Anastasiia Grishina, Leon Moonen

Large language models trained on source code can support a variety of software development tasks, such as code recommendation and program repair. Large amounts of data for training…

cs.SE2023★ 15 cited

The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification

Anastasiia Grishina, Max Hort, Leon Moonen

The use of modern Natural Language Processing (NLP) techniques has shown to be beneficial for software engineering tasks, such as vulnerability detection and type inference. Howeve…

cs.SE2023★ 43 cited

Fully Autonomous Programming with Large Language Models

Vadim Liventsev, Anastasiia Grishina, Aki Härmä +1

Current approaches to program synthesis with Large Language Models (LLMs) exhibit a "near miss syndrome": they tend to generate programs that semantically resemble the correct answ…

cs.SE2022★ 6 cited

Enabling Automatic Repair of Source Code Vulnerabilities Using Data-Driven Methods

Anastasiia Grishina

Users around the world rely on software-intensive systems in their day-to-day activities. These systems regularly contain bugs and security vulnerabilities. To facilitate bug fixin…

cs.SE2021

Towards More Reliable Automated Program Repair by Integrating Static Analysis Techniques

Omar I. Al-Bataineh, Anastasiia Grishina, Leon Moonen

A long-standing open challenge for automated program repair is the overfitting problem, which is caused by having insufficient or incomplete specifications to validate whether a ge…