Benedikt Fein

Orcid: 0000-0002-3798-845X

According to our database1, Benedikt Fein authored at least 12 papers between 2022 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Challenges of deploying code embeddings: an industrial case study on method name generation.
Autom. Softw. Eng., December, 2026

Challenges of Deploying Code Embeddings in Industry: An Industrial Case Study on Method Name Generation [Artefact].
Dataset, January, 2026

[Replication Package] Reasoning About Bugs in Learners' Scratch Programs Using Large Language Models.
Dataset, January, 2026

2025
LitterBox+: An Extensible Framework for LLM-enhanced Scratch Static Code Analysis.
CoRR, September, 2025

Detecting Gender Stereotypes in Scratch Programming Tutorials.
Dataset, September, 2025

AsserT5: Test Assertion Generation Using a Fine-Tuned Code Language Model (Replication Package).
Dataset, February, 2025

Detecting Gender Stereotypes in Scratch Programming Tutorials.
Proceedings of the 25th Koli Calling International Conference on Computing Education Research, 2025

LitterBox<sup>+</sup>: An Extensible Framework for LLM-enhanced Scratch Static Code Analysis.
Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering, 2025

AsserT5: Test Assertion Generation Using a Fine-Tuned Code Language Model.
Proceedings of the IEEE/ACM International Conference on Automation of Software Test, 2025

2023
On the Applicability of Language Models to Block-Based Programs.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

2022
CATNIP: An Automated Hint Generation Tool for Scratch.
Proceedings of the ITiCSE 2022: Innovation and Technology in Computer Science Education, Dublin, Ireland, July 8, 2022

An Evaluation of code2vec Embeddings for Scratch.
Proceedings of the 15th International Conference on Educational Data Mining, 2022


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