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Part 1: Document Description
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Citation |
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Title: |
Replication data for "Analyzing the Potency of Pretrained Transformer Models for Automated Program Repair" |
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Identification Number: |
doi:10.60507/FK2/O54LWP |
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Distributor: |
bonndata |
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Date of Distribution: |
2024-07-15 |
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Version: |
2 |
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Bibliographic Citation: |
Leiwig, Maximilian; Swierzy, Ben; Bungartz, Christian; Meier, Michael, 2024, "Replication data for "Analyzing the Potency of Pretrained Transformer Models for Automated Program Repair"", https://doi.org/10.60507/FK2/O54LWP, bonndata, V2 |
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Citation |
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Title: |
Replication data for "Analyzing the Potency of Pretrained Transformer Models for Automated Program Repair" |
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Identification Number: |
doi:10.60507/FK2/O54LWP |
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Authoring Entity: |
Leiwig, Maximilian (University of Bonn, Lamarr Institute) |
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Swierzy, Ben (University of Bonn) |
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Bungartz, Christian (University of Bonn, Lamarr Institute) |
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Meier, Michael (University of Bonn, Fraunhofer FKIE, Lamarr Institute) |
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Distributor: |
bonndata |
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Access Authority: |
Leiwig, Maximilian |
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Depositor: |
Leiwig, Maximilian |
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Date of Deposit: |
2024-07-08 |
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Holdings Information: |
https://doi.org/10.60507/FK2/O54LWP |
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Study Scope |
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Keywords: |
Computer and Information Science, Computer and Information Science |
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Abstract: |
This repository contains replication data for the paper "Analyzing the Potency of Pretrained Transformer Models for Automated Program Repair".<br> The dataset contains commits that indicate a bug fix from 200 repositories on Github. Scripts for fetching data associated with the commits are available (see Github repository linked under "Related Material"). <hr> File descriptions: <ul> <li><code>repositories.csv</code>: List of repository names with metadata</li> <li><code>commits.csv</code>: List of commit identifiers of the 200 repositories with most bug fixing commits</li> <li><code>commits_high_watch_count.csv</code>: List of commit identifiers of the 200 repositories with most bug fixing commits with a watch count of at least 50</li> </ul> <hr> Icon licensed under CC-BY by xinh.studio |
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Kind of Data: |
quantitative |
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Notes: |
The corresponding paper was be published at SEAA Aug 28 - Aug 30 2024. |
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Methodology and Processing |
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Sources Statement |
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Documentation and Access to Sources: |
Original Sources are Google BigQuery and GitHub |
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Data Access |
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Other Study Description Materials |
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Related Materials |
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Code: https://github.com/Synrom/FixMe |
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Related Publications |
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Citation |
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Title: |
M. Leiwig, B. Swierzy, C. Bungartz and M. Meier, "Analyzing the Potency of Pretrained Transformer Models for Automated Program Repair," 2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), Paris, France, 2024, pp. 72-79, doi: 10.1109/SEAA64295.2024.00020. |
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Identification Number: |
10.1109/SEAA64295.2024.00020. |
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Bibliographic Citation: |
M. Leiwig, B. Swierzy, C. Bungartz and M. Meier, "Analyzing the Potency of Pretrained Transformer Models for Automated Program Repair," 2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), Paris, France, 2024, pp. 72-79, doi: 10.1109/SEAA64295.2024.00020. |
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Label: |
commits.csv |
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Notes: |
text/csv |
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Label: |
commits_high_watch_count.csv |
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Notes: |
text/csv |
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Label: |
README.md |
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Notes: |
text/markdown |
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Label: |
repositories.csv |
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Notes: |
text/csv |