The application of data analytics and machine learning techniques in predicting critical software process parameters
The overall approach is summarized in the following paper:
Dam H. K., T. Tran, J. Grundy and A. K. Ghose, DeepSoft: A vision for a deep model of software. In Proceedings of the 24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE) , Visions and Reflections Track, ACM Press
The application of AI techniques, such as intelligent search, in its various forms to software engineering problems
The application of social media mining techniques to platforms such as StackOverflow.
Some recent publications:
Choetkiertikul M., H. K. Dam, T. Tran, A. K. Ghose, and J. Grundy. Predicting Delivery Capability in Iterative Software Development. IEEE Transactions on Software Engineering, doi.org/10.1109/TSE.2017.2693989
M. Choetkiertikul, H. K. Dam, T. Tran, T. Pham, A. K. Ghose, and T. Menzies, “A deep learning model for estimating story points”, IEEE Transactions on Software Engineering, DOI:10.1109/TSE.2018.2792473
Choetkiertikul M., H. K. Dam, T. Tran and A. K. Ghose. Predicting the delay of issues with due dates in software projects.Empirical Software Engineering Journal, Volume 22, Issue 3, pages 1223-1263, Springer.
M. Choetkiertikul, H. Dam, T. Tran and A.K. Ghose. Characterization and prediction of issue-related risks in software projects. In Proceedings of 12th Working Conference on Mining Software Repositories (MSR-2015), co-located with ICSE-2015, pages 280 - 291, IEEE. (ACM SIGSOFT Distinguished Paper Award).
H. Dam, B. T. R. Savarimuthu, D. Avery and A. K. Ghose. Mining Software Repositories for Social Norms. In Proceedings of the 37th International Conference on Software Engineering (ICSE-2015), New Ideas and Emerging Results Track, IEEE.