Testifiers produce research that is publicized in various conferences and journals. Here is a chronological list of these contributions:
A. Arrieta, S. Wang, G. Sagardui, U. Markiegi, L. Etxeberria and A. Arruabarrena. Pareto efficient multi-objective black-box test case selection for simulation-based testing. Information and Software Technology, vol 114, pp. 137-154, 2019.
D. Pradhan, S. Wang, S. Ali, T. Yue and M. Liaaen. Employing Rule Mining and Multi-Objective Search for Dynamic Test Case Prioritization. Journal of Systems and Software (JSS), vol 153, pp. 86-104, 2019.
D. Pradhan, S. Wang, S. Ali, T. Yue and M. Liaaen. Search-Based Test Case Implantation for Testing Untested Configurations. Information and Software Technology, vol 111, pp. 22-36, 2019.
Tan, Chao; Behjati, Razieh; Arisholm, Erik. A model-based approach to generate dynamic synthetic test data: A conceptual model. In: 2019 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW). IEEE, 2019. p. 11-14.
Tan, Chao. A Model-Based Approach to Generate Dynamic Synthetic Test Data. In: 2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST). IEEE, 2019. p. 495-497.
Razieh Behjati, Erik Arisholm, Margrethe M. Bedregal, and Chao Tan. 2019. Synthetic test data generation using recurrent neural networks: a position paper. In Proceedings of the 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE ’19). IEEE Press, Piscataway, NJ, USA, 22-27.
E. Rogstad, E. Arisholm, L. Briand, R. Dalberg and M. Rynning, Industrial Experiences With Automated Regression Testing of a Legacy Database Application, IEEE Int. Conference on Software Maintenance, 2011