Sustainable Training of Code Language Models through Data Refinement

Información del proyecto

condenSE

Identificador del acuerdo de subvención: 101151798

DOI

10.3030/101151798

Proyecto cerrado

Fecha de la firma de la CE 6 Marzo 2024

Fecha de inicio 1 Abril 2024

Fecha de finalización 31 Marzo 2026

Financiado con arreglo a

• Marie Skłodowska-Curie Actions (MSCA)

Coste total

Sin datos

Aportación de la UE

€ 210 911,04

Coordinado por

SIMULA RESEARCH LABORATORY AS
Norway

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Documents, reports (1)

Communication, Dissemination & Exploitation Plan

The plan describes the planned measures to maximize the impact of the project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measures and public engagement strategy, the aim is to inform and reach out to society and show the activities performed, and the use and the benefits the project will have for citizens.

Data Management Plan (1)

Data Management Plan

The Data Management Plan describes the data management life cycle for all data sets that will be collected, processed or generated by the action. It is a document describing what data will be collected, processed or generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved.

Publicaciones

Conference proceedings (5)

Semantic-Preserving Transformations as Mutation Operators: A Study on Their Effectiveness in Defect Detection

Autores: Max Hort, Linas Vidziunas, Leon Moonen
Publicado en: 2025 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 2025
Editor: IEEE
DOI: 10.1109/ICSTW64639.2025.10962512

The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models

Autores: Fernando Vallecillos Ruiz; Max Hort; Leon Moonen
Publicado en: Proceedings of the 29th International Conference on Evaluation and Assessment in Software Engineering, 2025
DOI: 10.48550/ARXIV.2505.02931

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

Autores: Roman Macháček, Anastasiia Grishina, Max Hort, Leon Moonen
Publicado en: 2025 IEEE International Conference on Software Maintenance and Evolution (ICSME), 2025
Editor: IEEE
DOI: 10.1109/ICSME64153.2025.00042

Codehacks: A Dataset of Adversarial Tests for Competitive Programming Problems Obtained from Codeforces

Autores: Max Hort, Leon Moonen
Publicado en: 2025 IEEE Conference on Software Testing, Verification and Validation (ICST), 2025
Editor: IEEE
DOI: 10.1109/ICST62969.2025.10988963

A Comparative Study on Large Language Models for Log Parsing

Autores: Merve Astekin; Max Hort; Leon Moonen
Publicado en: Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2024
DOI: 10.48550/ARXIV.2409.02474

Peer reviewed articles (2)

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

Autores: Fernando Vallecillos Ruiz, Anastasiia Grishina, Max Hort, Leon Moonen
Publicado en: ACM Transactions on Software Engineering and Methodology, 2025, ISSN 1049-331X
Editor: Association for Computing Machinery (ACM)
DOI: 10.1145/3771922

Fairst: A Novel Approach for Machine Learning Bias Repair Through Latent Sensitive Attribute Translation

Autores: Carmen Meinson; Max Hort; Federica Sarro
Publicado en: Information and Software Technology, 2025, ISSN 1873-6025
Editor: Elsevier B.V.
DOI: 10.1016/J.INFSOF.2025.107900