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Most recent publications

S. Pugh, D. Binkley and L. Moonen

The Case for Adaptive Change Recommendation

In IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM). IEEE, 2018.
Proceedings, refereed
2018
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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.
Proceedings, refereed
2018
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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.
Journal Article
2018
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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.
Journal Article
2018
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Selected publications

T. G. Rolfsnes, S. Di Alesio, R. Behjati, L. Moonen and D. Binkley

Generalizing the Analysis of Evolutionary Coupling for Software Change Impact Analysis

In 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER). IEEE, 2016.
Proceedings, refereed
2016
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L. Moonen

Towards Evidence-Based Recommendations to Guide the Evolution of Component-Based Product Families

Science of Computer Programming 97 (2015): 105-112.
Journal Article
2015
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L. Moonen

Generating Robust Parsers Using Island Grammars

In Proceedings 8th Working Conference on Reverse Engineering. IEEE, 2001.
Proceedings, refereed
2001
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A. Yamashita and L. Moonen

Do Code Smells Reflect Important Maintainability Aspects?

In International Conference on Software Maintenance (ICSM). IEEE, 2012.
Proceedings, refereed
2012
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News

Thomas Rolfsnes (Photo: Simula/Karoline Hagane)
25 August 2017

Thomas Gramstad Rolfsnes successfully defended his PhD

On Friday September 1st, Thomas Gramstad Rolfsnes defended his PhD thesis "Improving History-Based Recommendation Systems for Software Evolution". The defense took place at 13:15 at...
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evolveIT: Evidence-Based Recommendations to Guide the Evolution of Component-Based Product Families

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2018

Journal articles

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.
Status: Published
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.
Status: Published

Proceedings, refereed

S. Pugh, D. Binkley and L. Moonen

The Case for Adaptive Change Recommendation

In IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM). IEEE, 2018.
Status: Accepted
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.
Status: Accepted

Miscellaneous

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.
Status: Published
2017

Proceedings, refereed

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. ACM/IEEE, 2017.
Status: Published
T. G. Rolfsnes, L. Moonen and D. Binkley

Predicting Relevance of Change Recommendations

In The IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 2017.
Status: Published

Talks, keynote

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.
Status: Published

Talks, invited

L. Moonen

History-Based Recommendations to Guide Software Evolution

In Graduate School of Information Science and Technology, Osaka University, Osaka, Japan., 2017.
Status: Published
L. Moonen

History-Based Recommendations to Guide Software Evolution

In National Institute of Advanced Industrial Science and Technology (AIST), Japan., 2017.
Status: Published