Sebastian Hönel | lnu.se

Publikationer

Artikel i tidskrift (Refereegranskat)

Hönel, S., Ericsson, M., Löwe, W., Wingkvist, A. (2020). Using source code density to improve the accuracy of automatic commit classification into maintenance activities. Journal of Systems and Software. 168. 1-19.

Konferensbidrag (Refereegranskat)

Hönel, S., Ericsson, M., Löwe, W., Wingkvist, A. (2019). Importance and Aptitude of Source code Density for Commit Classification into Maintenance Activities. 2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS). 109-120.
Ulan, M., Hönel, S., Martins, R.M., Ericsson, M., Löwe, W., et al. (2018). Quality Models Inside Out : Interactive Visualization of Software Metrics by Means of Joint Probabilities. Proceedings of the 2018 Sixth IEEE Working Conference on Software Visualization, (VISSOFT), Madrid, Spain, 2018. 65-75.
Hönel, S., Ericsson, M., Löwe, W., Wingkvist, A. (2018). A changeset-based approach to assess source code density and developer efficacy. ICSE '18 Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings. 220-221.

Dataset (Refereegranskat)

Hönel, S. (2019). 359,569 commits with source code density; 1149 commits of which have software maintenance activity labels (adaptive, corrective, perfective).

Övrigt (Refereegranskat)

Hönel, S. (2020). mmb: Arbitrary Dependency Mixed Multivariate Bayesian Models.
Ulan, M., Hönel, S., Martins, R.M., Ericsson, M., Löwe, W., et al. (2018). Artifact: Quality Models Inside Out: Interactive Visualization of Software Metrics by Means of Joint Probabilities.

Konferensbidrag (Övrigt vetenskapligt)

Hönel, S., Ericsson, M., Löwe, W., Wingkvist, A. (2019). Bayesian Regression on segmented data using Kernel Density Estimation. 5th annual Big Data Conference : Linnaeus University, Växjö, Sweden, 5-6 December 2019.

Övrigt (Övrigt vetenskapligt)

Hönel, S. (2020). Git Density: Analyze git repositories to extract the Source Code Density and other Commit Properties.

Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)

Hönel, S. (2020). Efficient Automatic Change Detection in Software Maintenance and Evolutionary Processes. Licentiate Thesis. Växjö, Faculty of Technology, Linnaeus University. 37.