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2018
T. G. Rolfsnes, L. Moonen, S. Di Alesio, R. Behjati and D. Binkley. "Aggregating Association Rules to Improve Change Recommendation." Journal of Empirical Software Engineering (EMSE) 23, no. 2 (2018): 987-1035.PDF icon aggregating_association_rules_to_improve_change_recommendation.pdf (3.6 MB)
S. Pugh, D. Binkley and L. Moonen. The Case for Adaptive Change Recommendation In 18th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM). IEEE, 2018.PDF icon the_case_for_adaptive_change_recommendation.pdf (255.87 KB)
L. Moonen, T. G. Rolfsnes, D. Binkley and S. Di Alesio. Data set for the paper What are the Effects of History Length and Age on Mining Software Change Impact?. Zenodo, 2018.
C. M. Rosenberg and L. Moonen. Improving Problem Identification via Automated Log Clustering using Dimensionality Reduction In 12th International Symposium on Empirical Software Engineering and Measurement (ESEM 2018). ACM, 2018.PDF icon improving_problem_identification_via_automated_log_clustering_using_dimensionality_reduction.pdf (879.26 KB)
C. M. Rosenberg and L. Moonen. On the Use of Automated Log Clustering to Support Effort Reduction in Continuous Engineering In 25th Asia-Pacific Software Engineering Conference (APSEC 2018). IEEE, 2018.PDF icon on_the_use_of_automated_log_clustering_to_support_effort_reduction_in_continuous_engineering.pdf (599.48 KB)
L. Moonen, T. G. Rolfsnes, D. Binkley and S. Di Alesio. "What are the Effects of History Length and Age on Mining Software Change Impact?" Journal of Empirical Software Engineering (EMSE) 23, no. 4 (2018): 2362-2397.PDF icon 10.1007_s10664-017-9588-z.pdf (1.39 MB)
2017
C. M. Rosenberg and L. Moonen. Certus Project 9 – Smarter Testing of Evolving Software Systems In 12th Certus User Partner Workshop, Norway., 2017.
L. Moonen. History-Based Recommendations to Guide Software Evolution In Nara Institute of Science and Technology, Nara, Japan., 2017.
L. Moonen. History-Based Recommendations to Guide Software Evolution In Kyoto Institute of Technology, Kyoto, Japan., 2017.
L. Moonen. History-Based Recommendations to Guide Software Evolution In Graduate School of Information Science and Technology, Osaka University, Osaka, Japan., 2017.
L. Moonen. History-Based Recommendations to Guide Software Evolution In Tokyo Institute of Technology, Tokyo, Japan., 2017.
L. Moonen. History-Based Recommendations to Guide Software Evolution In National Institute of Advanced Industrial Science and Technology (AIST), Japan., 2017.
L. Moonen. Leveraging Machine Learning to Guide Software Evolution In 8th IEEE International Workshop on Empirical Software Engineering in Practice (IWESEP), Tokyo, Japan. Tokyo, Japan: IEEE, 2017.
T. G. Rolfsnes, L. Moonen and D. Binkley. Predicting Relevance of Change Recommendations In The IEEE/ACM International Conference on Automated Software Engineering (ASE), Edited by G. Ruso, M. Di Penta and T. N. Nguyen. IEEE, 2017.PDF icon predicting_relevance_of_change_recommendations.pdf (379.76 KB)
T. G. Rolfsnes, L. Moonen and D. Binkley. Predicting Relevance of Change Recommendations In IEEE/ACM International Conference on Automated Software Engineering (ASE), Urbana-Champaign, Illinois, USA. IEEE, 2017.
J. L. de la Vara, M. Borg, K. Wnuk and L. Moonen. Safety Evidence Change Impact Analysis in Practice In International Conference on Software Engineering, Edited by S. Uchitel, A. Orso and M. P. Robillard. ACM/IEEE, 2017.
J. L. de la Vara, M. Borg, K. Wnuk and L. Moonen. Safety Evidence Change Impact Analysis in Practice In International Conference on Software Engineering, Buenos Aires, Argentina. ACM/IEEE, 2017.

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