Empirical Software Engineering

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Springer
 
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  • 2023 | Journal Article | 
    ​ ​What really changes when developers intend to improve their source code: a commit-level study of static metric value and static analysis warning changes​
    Trautsch, A.; Erbel, J.; Herbold, S. & Grabowski, J.​ (2023) 
    Empirical Software Engineering, 28(2).​ DOI: https://doi.org/10.1007/s10664-022-10257-9 
    ​Details  DOI 
  • 2023 | Journal Article | 
    ​ ​Are automated static analysis tools worth it? An investigation into relative warning density and external software quality on the example of Apache open source projects​
    Trautsch, A.; Herbold, S. & Grabowski, J.​ (2023) 
    Empirical Software Engineering, 28(3).​ DOI: https://doi.org/10.1007/s10664-023-10301-2 
    ​Details  DOI 
  • 2023 | Journal Article | 
    ​ ​Differential testing for machine learning: an analysis for classification algorithms beyond deep learning​
    Herbold, S. & Tunkel, S.​ (2023) 
    Empirical Software Engineering, 28(2).​ DOI: https://doi.org/10.1007/s10664-022-10273-9 
    ​Details  DOI 
  • 2022 | Journal Article | 
    ​ ​A fine-grained data set and analysis of tangling in bug fixing commits​
    Herbold, S.; Trautsch, A.; Ledel, B.; Aghamohammadi, A.; Ghaleb, T. A.; Chahal, K. K. & Bossenmaier, T. et al.​ (2022) 
    Empirical Software Engineering, 27(6).​ DOI: https://doi.org/10.1007/s10664-021-10083-5 
    ​Details  DOI 
  • 2022 | Journal Article | 
    ​ ​Smoke testing for machine learning: simple tests to discover severe bugs​
    Herbold, S. & Haar, T.​ (2022) 
    Empirical Software Engineering, 27(2) art. 45​.​ DOI: https://doi.org/10.1007/s10664-021-10073-7 
    ​Details  DOI 
  • 2022 | Journal Article | 
    ​ ​Problems with SZZ and features: An empirical study of the state of practice of defect prediction data collection​
    Herbold, S.; Trautsch, A.; Trautsch, F. & Ledel, B.​ (2022) 
    Empirical Software Engineering, 27(2) art. 42​.​ DOI: https://doi.org/10.1007/s10664-021-10092-4 
    ​Details  DOI 
  • 2022 | Journal Article | 
    ​ ​Exploring the relationship between performance metrics and cost saving potential of defect prediction models​
    Tunkel, S. & Herbold, S. ​ (2022) 
    Empirical Software Engineering, 27(7).​ DOI: https://doi.org/10.1007/s10664-022-10224-4 
    ​Details  DOI 
  • 2020 | Journal Article | Research Paper | 
    ​ ​A longitudinal study of static analysis warning evolution and the effects of PMD on software quality in Apache open source projects​
    Trautsch, A. ; Herbold, S.   & Grabowski, J. ​ (2020) 
    Empirical Software Engineering, 25(6) pp. 5137​-5192​.​ DOI: https://doi.org/10.1007/s10664-020-09880-1 
    ​Details  DOI 
  • 2020 | Journal Article | Erratum | 
    ​ ​Correction to: On the feasibility of automated prediction of bug and non-bug issues​
    Herbold, S. ; Trautsch, A.   & Trautsch, F. ​ (2020) 
    Empirical Software Engineering, 25(6) pp. 5370​-5373​.​ DOI: https://doi.org/10.1007/s10664-020-09888-7 
    ​Details  DOI 
  • 2020 | Journal Article | 
    ​ ​On the feasibility of automated prediction of bug and non-bug issues​
    Herbold, S. ; Trautsch, A.   & Trautsch, F. ​ (2020) 
    Empirical Software Engineering, 25(6) pp. 5333​-5369​.​ DOI: https://doi.org/10.1007/s10664-020-09885-w 
    ​Details  DOI 
  • 2017 | Journal Article
    ​ ​Addressing problems with replicability and validity of repository mining studies through a smart data platform​
    Trautsch, F. ; Herbold, S. ; Makedonski, P.   & Grabowski, J. ​ (2017) 
    Empirical Software Engineering, 23(2) pp. 1036​-1083​.​ DOI: https://doi.org/10.1007/s10664-017-9537-x 
    ​Details  DOI 
  • 2016 | Journal Article
    ​ ​Global vs. local models for cross-project defect prediction​
    Herbold, S. ; Trautsch, A.   & Grabowski, J. ​ (2016) 
    Empirical Software Engineering, 22(4) pp. 1866​-1902​.​ DOI: https://doi.org/10.1007/s10664-016-9468-y 
    ​Details  DOI 
  • 2011 | Journal Article | 
    ​ ​Calculation and optimization of thresholds for sets of software metrics​
    Herbold, S. ; Grabowski, J.   & Waack, S. ​ (2011) 
    Empirical Software Engineering, 16(6) pp. 812​-841​.​ DOI: https://doi.org/10.1007/s10664-011-9162-z 
    ​Details  DOI  WoS 

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