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ORCIDTaylor R. Schorlemmer
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2020 – today
- 2024
[c8]Taylor R. Schorlemmer, Kelechi G. Kalu, Luke Chigges, Kyung Myung Ko, Eman Abu Ishgair, Saurabh Bagchi, Santiago Torres-Arias, James C. Davis:
Signing in Four Public Software Package Registries: Quantity, Quality, and Influencing Factors. SP 2024: 1160-1178- [i8]Taylor R. Schorlemmer, Kelechi G. Kalu, Luke Chigges, Kyung Myung Ko, Eman Abdul-Muhd Abu Isghair, Saurabh Baghi, Santiago Torres-Arias, James C. Davis:
Signing in Four Public Software Package Registries: Quantity, Quality, and Influencing Factors. CoRR abs/2401.14635 (2024) - [i7]James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer, Nicholas Synovic, George K. Thiruvathukal:
Reusing Deep Learning Models: Challenges and Directions in Software Engineering. CoRR abs/2404.16688 (2024) - [i6]Chinenye Okafor, Taylor R. Schorlemmer, Santiago Torres-Arias, James C. Davis:
SoK: Analysis of Software Supply Chain Security by Establishing Secure Design Properties. CoRR abs/2406.10109 (2024) - [i5]Taylor R. Schorlemmer, Ethan H. Burmane, Kelechi G. Kalu, Santiago Torres-Arias, James C. Davis:
Establishing Provenance Before Coding: Traditional and Next-Gen Signing. CoRR abs/2407.03949 (2024) - 2023
- [c7]Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis:
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. ICSE 2023: 2463-2475 - [c6]James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer, Nicholas Synovic, George K. Thiruvathukal:
Reusing Deep Learning Models: Challenges and Directions in Software Engineering. JVA 2023: 17-30 - [c5]Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis:
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages. MSR 2023: 57-61 - [c4]Tanmay Singla
, Dharun Anandayuvaraj, Kelechi G. Kalu, Taylor R. Schorlemmer, James C. Davis:
An Empirical Study on Using Large Language Models to Analyze Software Supply Chain Security Failures. SCORED@CCS 2023: 5-15 - [c3]Kelechi G. Kalu, Taylor R. Schorlemmer, Sophie Chen, Kyle A. Robinson, Erik Kocinare, James C. Davis:
Reflecting on the Use of the Policy-Process-Product Theory in Empirical Software Engineering. ESEC/SIGSOFT FSE 2023: 2112-2116 - [i4]Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis:
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. CoRR abs/2303.02552 (2023) - [i3]Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis:
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages. CoRR abs/2303.08934 (2023) - [i2]Tanmay Singla, Dharun Anandayuvaraj, Kelechi G. Kalu, Taylor R. Schorlemmer, James C. Davis:
An Empirical Study on Using Large Language Models to Analyze Software Supply Chain Security Failures. CoRR abs/2308.04898 (2023) - [i1]Kelechi G. Kalu, Taylor R. Schorlemmer, Sophie Chen, Kyle A. Robinson, Erik Kocinare, James C. Davis:
Reflecting on the Use of the Policy-Process-Product Theory in Empirical Software Engineering. CoRR abs/2308.12387 (2023) - 2022
- [c2]Chinenye Okafor, Taylor R. Schorlemmer, Santiago Torres-Arias, James C. Davis:
SoK: Analysis of Software Supply Chain Security by Establishing Secure Design Properties. SCORED@CCS 2022: 15-24 - [c1]Wenxin Jiang, Nicholas Synovic, Rohan Sethi, Aryan Indarapu, Matt Hyatt, Taylor R. Schorlemmer, George K. Thiruvathukal, James C. Davis:
An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain. SCORED@CCS 2022: 105-114
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