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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} }
Error Detection, Change-Based Code Analysis, API Misuses, Pattern Mining
Error Detection, Change-Based Code Analysis, API Misuses, Pattern Mining
| 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). | 1 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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