Christopher R. Theisen

Yu, Z., Theisen, C., Williams, L., & Menzies, T. (2021). Improving Vulnerability Inspection Efficiency Using Active Learning. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 47(11), 2401–2420. https://doi.org/10.1109/TSE.2019.2949275

Theisen, C., & Williams, L. (2020). Better together: Comparing vulnerability prediction models. INFORMATION AND SOFTWARE TECHNOLOGY, 119. https://doi.org/10.1016/j.infsof.2019.106204

Theisen, C., Munaiah, N., Al-Zyoud, M., Carver, J. C., Meneely, A., & Williams, L. (2018). [Review of Attack surface definitions: A systematic literature review]. INFORMATION AND SOFTWARE TECHNOLOGY, 104, 94–103. https://doi.org/10.1016/j.infsof.2018.07.008

Choi, H.-M., & Ji, C.-R. (2017). Twist-3 Distribution Amplitudes of Pion in the Light-Front Quark Model. Few-Body Systems, 58(2). https://doi.org/10.1007/s00601-016-1208-8

Theisen, C. (2016). Reusing stack traces: Automated attack surface approximation. 2016 IEEE/ACM 38th International Conference on Software Engineering Companion (ICSE-C), 859–862.

Theisen, C., & Williams, L. (2016). Stack traces reveal attack surfaces. Perspectives on Data Science for Software Engineering, 73–76.

Theisen, C. (2015). Automated attack surface approximation. 2015 10th Joint Meeting of the European Software Engineering Conference and the ACM Sigsoft Symposium on the Foundations of Software Engineering (ESEC/FSE 2015) Proceedings, 1063–1065.