<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"><identifier identifierType="DOI">10.60507/FK2/O54LWP</identifier><creators><creator><creatorName nameType="Personal">Leiwig, Maximilian</creatorName><givenName>Maximilian</givenName><familyName>Leiwig</familyName><nameIdentifier SchemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">0009-0006-5703-5708</nameIdentifier><affiliation>University of Bonn, Lamarr Institute</affiliation></creator><creator><creatorName nameType="Personal">Swierzy, Ben</creatorName><givenName>Ben</givenName><familyName>Swierzy</familyName><nameIdentifier SchemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">0009-0003-0485-4791</nameIdentifier><affiliation>University of Bonn</affiliation></creator><creator><creatorName nameType="Personal">Bungartz, Christian</creatorName><givenName>Christian</givenName><familyName>Bungartz</familyName><nameIdentifier SchemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">0009-0008-0576-8744</nameIdentifier><affiliation>University of Bonn, Lamarr Institute</affiliation></creator><creator><creatorName nameType="Personal">Meier, Michael</creatorName><givenName>Michael</givenName><familyName>Meier</familyName><nameIdentifier SchemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">0009-0006-8199-5004</nameIdentifier><affiliation>University of Bonn, Fraunhofer FKIE, Lamarr Institute</affiliation></creator></creators><titles><title>Replication data for "Analyzing the Potency of Pretrained Transformer Models for Automated Program Repair"</title></titles><publisher>bonndata</publisher><publicationYear>2024</publicationYear><subjects><subject>Computer and Information Science</subject></subjects><contributors><contributor contributorType="ContactPerson"><contributorName nameType="Personal">Leiwig, Maximilian</contributorName><givenName>Maximilian</givenName><familyName>Leiwig</familyName><affiliation>University of Bonn</affiliation></contributor></contributors><dates><date dateType="Submitted">2024-07-08</date><date dateType="Updated">2025-01-14</date></dates><resourceType resourceTypeGeneral="Dataset">quantitative</resourceType><relatedIdentifiers><relatedIdentifier relationType="IsSupplementTo" relatedIdentifierType="DOI">10.1109/SEAA64295.2024.00020.</relatedIdentifier></relatedIdentifiers><sizes><size>1945</size><size>6963520</size><size>1567538</size><size>3144907</size></sizes><formats><format>text/markdown</format><format>text/csv</format><format>text/csv</format><format>text/csv</format></formats><version>2.0</version><rightsList><rights rightsURI="info:eu-repo/semantics/openAccess"/><rights rightsURI="http://creativecommons.org/licenses/by/4.0">CC BY 4.0</rights></rightsList><descriptions><description descriptionType="Abstract">This repository contains replication data for the paper "Analyzing the Potency of Pretrained Transformer Models for Automated Program Repair".&lt;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").
&lt;hr>

File descriptions:
&lt;ul>
&lt;li>&lt;code>repositories.csv&lt;/code>: List of repository names with metadata&lt;/li>
&lt;li>&lt;code>commits.csv&lt;/code>: List of commit identifiers of the 200 repositories with most bug fixing commits&lt;/li>
&lt;li>&lt;code>commits_high_watch_count.csv&lt;/code>: List of commit identifiers of the 200 repositories with most bug fixing commits with a watch count of at least 50&lt;/li>
&lt;/ul>

&lt;hr>
Icon licensed under CC-BY by xinh.studio</description><description descriptionType="Methods">Original Sources are Google BigQuery and GitHub</description><description descriptionType="Other">The corresponding paper was be published at SEAA Aug 28 - Aug 30 2024.</description></descriptions><geoLocations/></resource>