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Replication Package for the master thesis "An Empirical Assessment on the Limits of Binary Code Summarisation with Transformer-based Models"

DOI:10.4121/20301309.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/20301309

Datacite citation style

Ali Al-Kaswan; Arie Van Deursen; Prem Devanbu; Ahmed, Toufique; Maliheh Izadi et. al. (2022): Replication Package for the master thesis "An Empirical Assessment on the Limits of Binary Code Summarisation with Transformer-based Models". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/20301309.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This dataset is published as part of the master thesis: "An Empirical Assessment on the Limits of Binary Code Summarisation with Transformer-based Models".
It includes both the training/evaluation data as well as trained models.


For more information, please refer to the data.md file or to the master thesis.

History

  • 2022-07-14 first online, published, posted

Publisher

4TU.ResearchData

Format

A 7zipped collection of: - 7zipped .jsonl files of training and evaluation data. - Trained pytorch_model.bin files

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems.

DATA

Files (2)