Towards the Automatic Classification of Traceability Links
C. Mills
Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017). To Appear

Automating Traceability Link Recovery Through Classification
C. Mills
ACM Student Research Competition, Proceedings of the 11th Joint Meeting on Foundations of Software Engineering (ESEC/FSE 2017), p.1068-1070.

Predicting Query Quality for Applications of Text Retrieval to Software Engineering Tasks
C. Mills, G. Bavota, S. Haiduc, R. Oliveto, A. Marcus, A. De Lucia
Transactions on Software Engineering and Methodology (TOSEM), 2017, 26(1), p.3.

A Machine Learning Approach for Determining the Validity of Traceability Links
C. Mills and S. Haiduc
in Proceedings of the 39th International Conference on Software Engineering Companion (ICSE Posters ’17), p.121-123.

The Impact of Retrieval Direction on IR-based Traceability Link Recovery
C. Mills and S. Haiduc
Proceedings of the 39th ACM/IEEE International Conference on Software Engineering: New Ideas and Emerging Results Track (ICSE-NIER 2017), p 51-54. 16.5% Acceptance Rate

Method of approximate fundamental solutions for ill-posed elliptic boundary value problems
Tian, H. Y., and C. Mills
Proceedings of Neural, Parallel and Scientific Computations, volume 4, 2010, pp. 373-378

NMR, IR/Raman, and Structural Properties in HO and RNO (R= Alkyl and Aryl) Metalloporphyrins with Implication for the HNOMyoglobin Complex
Y. Ling, C. Mills, R. Weber, L. Yang, and Y. Zhang
The Journal of the American Chemical Society, vol. 132, no. 5, 2010, pp. 1583-159