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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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Replication Package for "Guided Pattern Mining for API Misuse Detection by Change-Based Code Analysis"

Authors: Nielebock, Sebastian; Heumüller, Robert; Schott, Kevin Michael; Ortmeier, Frank;

Replication Package for "Guided Pattern Mining for API Misuse Detection by Change-Based Code Analysis"

Abstract

This repository provides the data sets and scripts used in the paper "Guided Pattern Mining for API Misuse Detection by Change-Based Code Analysis" by Sebastian Nielebock, Robert Heumüller, Kevin Michael Schott, and Frank Ortmeier from the Faculty of Computer Science of the Otto-von-Guericke University Magdeburg, Germany. The paper has been submitted for publication at Springer's "Automated Software Engineering - An International Journal" in August 2020. A preprint is available under https://arxiv.org/abs/2008.00277. All scripts and data sets are provided by the authors and come without any guarantee. For any issues regarding replication do not hesitate to contact us ({sebastian.nielebock,robert.heumueller, kevin.schott, frank.ortmeier} <at> ovgu.de) If you use or refer to these datasets, please cite our paper using the following BibTex entry. @misc{nielebock2020guided, title={Guided Pattern Mining for API Misuse Detection by Change-Based Code Analysis}, author={Sebastian Nielebock and Robert Heumüller and Kevin Michael Schott and Frank Ortmeier}, year={2020}, eprint={2008.00277}, archivePrefix={arXiv}, primaryClass={cs.SE} }

Related Organizations
Keywords

Error Detection, Change-Based Code Analysis, API Misuses, Pattern Mining

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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1
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8