TY - GEN
T1 - ModelMine
T2 - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020
AU - Reza, Sayed Mohsin
AU - Badreddin, Omar
AU - Rahad, Khandoker
N1 - Publisher Copyright:
© 2020 Owner/Author.
PY - 2020/10/16
Y1 - 2020/10/16
N2 - Mining Software Repositories (MSR) has opened up new pathways and rich sources of data for research and practical purposes. This research discipline facilitates mining data from open source repositories and analyzing software defects, development activities, processes, patterns, and more. Contemporary mining tools are geared towards data extraction, analysis primarily from textual artifacts and have limitations in representation, ranking and availability. This paper presents ModelMine, a novel mining tool focuses on mining model-based artifacts and designs from open source repositories. ModelMine is designed particularly to mine software repositories, artifacts and commit history to uncover information about software designs and practices in open-source communities. ModelMine supports features that include identification and ranking of open source repositories based on the extent of presence of model-based artifacts and querying repositories to extract models and design artifacts based on customizable criteria. It supports phase-by-phase caching of intermediate results to speed up the processing to enable efficient mining of data. We compare ModelMine against a state-of-the-art tool named PyDriller in terms of performance and usability. The results show that ModelMine has the potential to become instrumental for cross-disciplinary research that combines modeling and design with repository mining and artifacts extraction. URL: https://www.smreza.com/projects/modelmine/
AB - Mining Software Repositories (MSR) has opened up new pathways and rich sources of data for research and practical purposes. This research discipline facilitates mining data from open source repositories and analyzing software defects, development activities, processes, patterns, and more. Contemporary mining tools are geared towards data extraction, analysis primarily from textual artifacts and have limitations in representation, ranking and availability. This paper presents ModelMine, a novel mining tool focuses on mining model-based artifacts and designs from open source repositories. ModelMine is designed particularly to mine software repositories, artifacts and commit history to uncover information about software designs and practices in open-source communities. ModelMine supports features that include identification and ranking of open source repositories based on the extent of presence of model-based artifacts and querying repositories to extract models and design artifacts based on customizable criteria. It supports phase-by-phase caching of intermediate results to speed up the processing to enable efficient mining of data. We compare ModelMine against a state-of-the-art tool named PyDriller in terms of performance and usability. The results show that ModelMine has the potential to become instrumental for cross-disciplinary research that combines modeling and design with repository mining and artifacts extraction. URL: https://www.smreza.com/projects/modelmine/
UR - http://www.scopus.com/inward/record.url?scp=85096786458&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85096786458&partnerID=8YFLogxK
U2 - 10.1145/3417990.3422006
DO - 10.1145/3417990.3422006
M3 - Conference contribution
AN - SCOPUS:85096786458
T3 - Proceedings - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020 - Companion Proceedings
SP - 441
EP - 450
BT - Proceedings - 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2020 - Companion Proceedings
PB - Association for Computing Machinery, Inc
Y2 - 16 October 2020 through 23 October 2020
ER -