| Using source code density to improve the accuracy of automatic commit classification into maintenance activities S Hönel, M Ericsson, W Löwe, A Wingkvist Journal of Systems and Software 168, 110673, 2020 | 23 | 2020 |
| Importance and aptitude of source code density for commit classification into maintenance activities S Hönel, M Ericsson, W Löwe, A Wingkvist 2019 IEEE 19th international conference on software quality, reliability and …, 2019 | 18 | 2019 |
| Quality models inside out: Interactive visualization of software metrics by means of joint probabilities M Ulan, S Hönel, RM Martins, M Ericsson, W Löwe, A Wingkvist, A Kerren 2018 IEEE Working Conference on Software Visualization (VISSOFT), 65-75, 2018 | 17 | 2018 |
| A changeset-based approach to assess source code density and developer efficacy S Hönel, M Ericsson, W Löwe, A Wingkvist Proceedings of the 40th International Conference on Software Engineering …, 2018 | 7 | 2018 |
| 359,569 commits with source code density; 1149 commits of which have software maintenance activity labels (adaptive, corrective, perfective) S Hönel | 6 | 2019 |
| Detection of the Fire Drill anti-pattern: 15 real-world projects with ground truth, issue-tracking data, source code density, models and code S Hönel, P Pícha, P Brada, L Rychtarova, J Danek | 5 | 2023 |
| Contextual Operationalization of Metrics as Scores: Is My Metric Value Good? S Hönel, M Ericsson, W Löwe, A Wingkvist 2022 IEEE 22nd International Conference on Software Quality, Reliability and …, 2022 | 5 | 2022 |
| Process anti-pattern detection–a case study P Pícha, S Hönel, P Brada, M Ericsson, W Löwe, A Wingkvist, J Daněk Proceedings of the 27th European Conference on Pattern Languages of Programs …, 2022 | 5 | 2022 |
| Technical Reports Compilation: Detecting the Fire Drill Anti-pattern Using Source Code and Issue-Tracking Data S Hönel arXiv preprint arXiv:2104.15090, 2021 | 4 | 2021 |
| Detection of the Fire Drill anti-pattern: Nine real-world projects with ground truth, issue-tracking data, source code density, models and code S Hönel, P Pícha, P Brada, L Rychtarova Zenodo. https://doi. org/10.5281/zenodo 4734053, 2021 | 4 | 2021 |
| Git Density 2020.2: Analyze Git Repositories To Extract the Source Code Density and Other Commit Properties S Hönel February. https://doi. org/10.5281/zenodo 3662768, 2020 | 4 | 2020 |
| Activity-Based Detection of (Anti-)Patterns: An Embedded Case Study of the Fire Drill S Hönel, P Picha, M Ericsson, P Brada, W Löwe, A Wingkvist e-Informatica Software Engineering Journal 18, 240106, 2024 | 3 | 2024 |
| Artifact: Quality Models Inside Out: Interactive Visualization of Software Metrics by Means of Joint Probabilities M Ulan, S Hönel, RM Martins, M Ericsson, W Löwe, A Wingkvist, A Kerren | 3 | 2018 |
| Metrics As Scores: A Tool-and Analysis Suite and Interactive Application for Exploring Context-Dependent Distributions S Hönel, M Ericsson, W Löwe, A Wingkvist Journal of Open Source Software 8 (88), 4913, 2023 | 2 | 2023 |
| Exploiting Relations, Sojourn-Times, and Joint Conditional Probabilities for Automated Commit Classification S Hönel International Conference on Software Technologies, 323-331, 2023 | 2 | 2023 |
| Leveraging Evolutionary Changes for Software Process Quality S Hönel arXiv preprint arXiv:2305.18061, 2023 | | 2023 |
| Quantifying Process Quality: The Role of Effective Organizational Learning in Software Evolution S Hönel Linnaeus University Press, 2023 | | 2023 |
| An Approach to Ordering Objectives and Pareto Efficient Solutions S Hönel, W Löwe arXiv preprint arXiv:2205.15291, 2022 | | 2022 |
| anti-pattern using Source Code S Hönel | | 2021 |
| anti-pattern using Source Code and issue-tracking data S Hönel arXiv preprint arXiv:2104.15090, 2021 | | 2021 |
Morgan EricssonLinnaeus UniversityVerified email at lnu.se
