Tracing known security vulnerabilities in software repositories–A Semantic Web enabled modeling approach SS Alqahtani, EE Eghan, J Rilling Science of Computer Programming 121, 153-175, 2016 | 64 | 2016 |
On the Co-evolution of ML Pipelines and Source Code-Empirical Study of DVC Projects A Barrak, EE Eghan, B Adams 2021 IEEE International Conference on Software Analysis, Evolution and …, 2021 | 41 | 2021 |
SV-AF—A Security Vulnerability Analysis Framework SS Alqahtani, EE Eghan, J Rilling 2016 IEEE 27th International Symposium on Software Reliability Engineering …, 2016 | 33 | 2016 |
Recovering semantic traceability links between APIs and security vulnerabilities: An ontological modeling approach SS Alqahtani, EE Eghan, J Rilling 2017 IEEE International Conference on Software Testing, Verification and …, 2017 | 24 | 2017 |
Onboarding vs. Diversity, Productivity, and Quality-Empirical Study of the OpenStack Ecosystem A Foundjem, EE Eghan, B Adams 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE …, 2021 | 16 | 2021 |
API trustworthiness: an ontological approach for software library adoption EE Eghan, SS Alqahtani, C Forbes, J Rilling Software Quality Journal 27, 969-1014, 2019 | 15 | 2019 |
Why do builds fail?—A conceptual replication study A Barrak, EE Eghan, B Adams, F Khomh Journal of Systems and Software 177, 110939, 2021 | 13 | 2021 |
On the impact of interlanguage dependencies in multilanguage systems empirical case study on java native interface applications (JNI) M Grichi, M Abidi, F Jaafar, EE Eghan, B Adams IEEE Transactions on Reliability 70 (1), 428-440, 2020 | 13 | 2020 |
On the Impact of Multi-language Development in Machine Learning Frameworks M Grichi, EE Eghan, B Adams 2020 IEEE International Conference on Software Maintenance and Evolution …, 2020 | 10 | 2020 |
The missing link–A semantic web based approach for integrating screencasts with security advisories EE Eghan, P Moslehi, J Rilling, B Adams Information and Software Technology 117, 106197, 2020 | 8 | 2020 |
Towards a change taxonomy for machine learning pipelines: Empirical study of ML pipelines and forks related to academic publications A Bhatia, EE Eghan, M Grichi, WG Cavanagh, ZM Jiang, B Adams Empirical Software Engineering 28 (3), 60, 2023 | 3 | 2023 |
Towards a Change Taxonomy for Machine Learning Systems A Bhatia, EE Eghan, M Grichi, WG Cavanagh, Z Ming, B Adams arXiv preprint arXiv:2203.11365, 2022 | 3 | 2022 |
A Semantic Web-Enabled Approach for Dependency Management EE Eghan, J Rilling International Journal of Software Engineering and Knowledge Engineering 32 …, 2022 | 1 | 2022 |
On the Impact of Inter-language Dependencies in Multi-language Systems. M Grichi, M Abidi, F Jaafar, EE Eghan, B Adams QRS, 509, 2020 | 1 | 2020 |
Dependency Management 2.0–A Semantic Web Enabled Approach EE Eghan Concordia University, 2019 | 1 | 2019 |
An Open Dataset for Onboarding new Contributors–Empirical Study of OpenStack Ecosystem A Foundjem, EE Eghan, B Adams 2021 IEEE/ACM 43rd International Conference on Software Engineering …, 2021 | | 2021 |
Empirical Study on the Software Engineering Practices in Open Source ML Package Repositories M Xiu, EE Eghan, Z Ming, B Adams arXiv preprint arXiv:2012.01403, 2020 | | 2020 |