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Ellis E. Eghan
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Year
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
642016
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
412021
SV-AF—A Security Vulnerability Analysis Framework
SS Alqahtani, EE Eghan, J Rilling
2016 IEEE 27th International Symposium on Software Reliability Engineering …, 2016
332016
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
242017
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
162021
API trustworthiness: an ontological approach for software library adoption
EE Eghan, SS Alqahtani, C Forbes, J Rilling
Software Quality Journal 27, 969-1014, 2019
152019
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
132020
Why do builds fail?—A conceptual replication study
A Barrak, EE Eghan, B Adams, F Khomh
Journal of Systems and Software 177, 110939, 2021
122021
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
102020
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
82020
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
32023
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
32022
A Semantic Web-Enabled Approach for Dependency Management
EE Eghan, J Rilling
International Journal of Software Engineering and Knowledge Engineering 32 …, 2022
12022
On the Impact of Inter-language Dependencies in Multi-language Systems.
M Grichi, M Abidi, F Jaafar, EE Eghan, B Adams
QRS, 509, 2020
12020
Dependency Management 2.0–A Semantic Web Enabled Approach
EE Eghan
Concordia University, 2019
12019
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
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