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2020 – today
- 2025
[j34]Steffen Herbold
, Brian Valerius, Anamaria Mojica-Hanke, Isabella Lex, Joel Mittel:
Legal Aspects for Software Developers Interested in Generative AI Applications. IEEE Softw. 42(2): 68-75 (2025)- [i38]Jonathan Drechsel, Steffen Herbold:
GRADIEND: Monosemantic Feature Learning within Neural Networks Applied to Gender Debiasing of Transformer Models. CoRR abs/2502.01406 (2025) - [i37]Frederic Blum, Steffen Herbold, Johann-Mattis List:
From Isolates to Families: Using Neural Networks for Automated Language Affiliation. CoRR abs/2502.11688 (2025) - [i36]Jonathan Drechsel, Anja Reusch, Steffen Herbold:
MAMUT: A Novel Framework for Modifying Mathematical Formulas for the Generation of Specialized Datasets for Language Model Training. CoRR abs/2502.20855 (2025) - 2024
- [j33]Lukas Schulte, Benjamin Ledel, Steffen Herbold:
Studying the explanations for the automated prediction of bug and non-bug issues using LIME and SHAP. Empir. Softw. Eng. 29(4): 93 (2024) - [j32]Zaheed Ahmed, Eike Schwass, Steffen Herbold, Fabian Trautsch, Jens Grabowski:
A new perspective on the competent programmer hypothesis through the reproduction of real faults with repeated mutations. Softw. Test. Verification Reliab. 34(3) (2024) - [j31]Steffen Herbold:
Semantic similarity prediction is better than other semantic similarity measures. Trans. Mach. Learn. Res. 2024 (2024) - [c34]Zlata Kikteva, Alexander Trautsch, Steffen Herbold, Annette Hautli-Janisz:
Question Type Prediction in Natural Debate. SIGDIAL 2024: 624-630 - [i35]Steffen Herbold, Brian Valerius, Anamaria Mojica-Hanke, Isabella Lex, Joel Mittel:
Legal Aspects for Software Developers Interested in Generative AI Applications. CoRR abs/2404.16630 (2024) - [i34]Steffen Herbold, Alexander Trautsch, Zlata Kikteva, Annette Hautli-Janisz:
Large Language Models can impersonate politicians and other public figures. CoRR abs/2407.12855 (2024) - [i33]Anamaria Mojica-Hanke, David Nader-Palacio, Denys Poshyvanyk, Mario Linares-Vásquez, Steffen Herbold:
Perspective of Software Engineering Researchers on Machine Learning Practices Regarding Research, Review, and Education. CoRR abs/2411.19304 (2024) - 2023
- [j30]Tomás Bruna, Heng Li, Joseph Guhlin, Daniel Honsel, Steffen Herbold, Mario Stanke, Natalia Nenasheva, Matthis Ebel, Lars Gabriel, Katharina Jasmin Hoff:
Galba: genome annotation with miniprot and AUGUSTUS. BMC Bioinform. 24(1): 327 (2023) - [j29]Alexander Trautsch, Johannes Erbel, Steffen Herbold, Jens Grabowski:
What really changes when developers intend to improve their source code: a commit-level study of static metric value and static analysis warning changes. Empir. Softw. Eng. 28(2): 30 (2023) - [j28]Steffen Herbold, Steffen Tunkel:
Differential testing for machine learning: an analysis for classification algorithms beyond deep learning. Empir. Softw. Eng. 28(2): 34 (2023) - [j27]Alexander Trautsch, Steffen Herbold, Jens Grabowski:
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. Empir. Softw. Eng. 28(3): 66 (2023) - [j26]Julian von der Mosel, Alexander Trautsch, Steffen Herbold:
On the Validity of Pre-Trained Transformers for Natural Language Processing in the Software Engineering Domain. IEEE Trans. Software Eng. 49(4): 1487-1507 (2023) - [c33]Zlata Kikteva, Alexander Trautsch, Patrick Katzer, Mirko Oest, Steffen Herbold, Annette Hautli-Janisz:
On the Impact of Reconstruction and Context for Argument Prediction in Natural Debate. ArgMining@EMNLP 2023: 100-106 - [c32]Steffen Herbold, Tobias Haar:
Smoke testing for machine learning: simple tests to discover severe bugs. Software Engineering 2023: 61-62 - [c31]Steffen Herbold, Alexander Trautsch, Fabian Trautsch, Benjamin Ledel:
Problems with with SZZ and Features: An empirical assessment of the state of practice of defect prediction data collection. Software Engineering 2023: 63-64 - [c30]Julian von der Mosel, Alexander Trautsch, Steffen Herbold:
On the validity of pre-trained transformers for natural language processing in the software engineering domain. Software Engineering 2023: 93-94 - [c29]Steffen Tunkel, Steffen Herbold:
Exploring the relationship between performance metrics and cost saving potential of defect prediction models. Software Engineering 2023: 119-120 - [c28]Laura Cabra-Acela, Anamaria Mojica-Hanke, Mario Linares-Vásquez, Steffen Herbold:
On Using Information Retrieval to Recommend Machine Learning Good Practices for Software Engineers. ESEC/SIGSOFT FSE 2023: 2142-2146 - [e2]Shane McIntosh, Eunjong Choi, Steffen Herbold:
Proceedings of the 19th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2023, San Francisco, CA, USA, 8 December 2023. ACM 2023 [contents] - [i32]Anamaria Mojica-Hanke, Andrea Bayona, Mario Linares-Vásquez, Steffen Herbold, Fabio A. González:
What are the Machine Learning best practices reported by practitioners on Stack Exchange? CoRR abs/2301.10516 (2023) - [i31]Lukas Schulte, Anamaria Mojica-Hanke, Mario Linares-Vásquez, Steffen Herbold:
An exploratory study of bug-introducing changes: what happens when bugs are introduced in open source software? CoRR abs/2304.05358 (2023) - [i30]Anne Hennig, Lukas Schulte, Steffen Herbold, Oksana Kulyk, Peter Mayer:
Understanding issues related to personal data and data protection in open source projects on GitHub. CoRR abs/2304.06367 (2023) - [i29]Steffen Herbold, Annette Hautli-Janisz, Ute Heuer, Zlata Kikteva, Alexander Trautsch:
AI, write an essay for me: A large-scale comparison of human-written versus ChatGPT-generated essays. CoRR abs/2304.14276 (2023) - [i28]Laura Cabra-Acela, Anamaria Mojica-Hanke, Mario Linares-Vásquez, Steffen Herbold:
On Using Information Retrieval to Recommend Machine Learning Good Practices for Software Engineers. CoRR abs/2308.12095 (2023) - [i27]Steffen Herbold:
Semantic similarity prediction is better than other semantic similarity measures. CoRR abs/2309.12697 (2023) - 2022
- [j25]Steffen Herbold, Alexander Trautsch, Fabian Trautsch, Benjamin Ledel:
Problems with SZZ and features: An empirical study of the state of practice of defect prediction data collection. Empir. Softw. Eng. 27(2): 42 (2022) - [j24]Steffen Herbold, Tobias Haar:
Smoke testing for machine learning: simple tests to discover severe bugs. Empir. Softw. Eng. 27(2): 45 (2022) - [j23]Steffen Herbold, Alexander Trautsch, Benjamin Ledel, Alireza Aghamohammadi, Taher Ahmed Ghaleb, Kuljit Kaur Chahal, Tim Bossenmaier, Bhaveet Nagaria, Philip Makedonski, Matin Nili Ahmadabadi, Kristóf Szabados, Helge Spieker, Matej Madeja, Nathaniel Hoy, Valentina Lenarduzzi, Shangwen Wang, Gema Rodríguez-Pérez, Ricardo Colomo Palacios, Roberto Verdecchia, Paramvir Singh, Yihao Qin, Debasish Chakroborti, Willard Davis, Vijay Walunj, Hongjun Wu, Diego Marcilio, Omar Alam, Abdullah Aldaeej, Idan Amit, Burak Turhan, Simon Eismann, Anna-Katharina Wickert, Ivano Malavolta, Matús Sulír, Fatemeh H. Fard, Austin Z. Henley, Stratos Kourtzanidis, Eray Tuzun, Christoph Treude, Simin Maleki Shamasbi, Ivan Pashchenko, Marvin Wyrich, James Davis, Alexander Serebrenik, Ella Albrecht, Ethem Utku Aktas, Daniel Strüber, Johannes Erbel:
A fine-grained data set and analysis of tangling in bug fixing commits. Empir. Softw. Eng. 27(6): 125 (2022) - [j22]Steffen Tunkel, Steffen Herbold:
Exploring the relationship between performance metrics and cost saving potential of defect prediction models. Empir. Softw. Eng. 27(7): 182 (2022) - [c27]Alexander Trautsch, Steffen Herbold:
Predicting Issue Types with seBERT. NLBSE 2022: 37-39 - [d12]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.1 Full. 1.2. GRO.data, 2022 [all versions]
- [d11]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 1.3. 1.2. GRO.data, 2022 [all versions] - [d10]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.2 Full. 1.1. GRO.data, 2022 [all versions] - [d9]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.2 Small. 1.1. GRO.data, 2022 [all versions] - [d8]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.1 Small. GRO.data, 2022 - [i26]Alexander Trautsch, Steffen Herbold:
Predicting Issue Types with seBERT. CoRR abs/2205.01335 (2022) - [i25]Steffen Herbold, Steffen Tunkel:
Differential testing for machine learning: an analysis for classification algorithms beyond deep learning. CoRR abs/2207.11976 (2022) - [i24]Benjamin Ledel, Steffen Herbold:
Studying the explanations for the automated prediction of bug and non-bug issues using LIME and SHAP. CoRR abs/2209.07623 (2022) - 2021
- [j21]Steffen Herbold, Aynur Amirfallah, Fabian Trautsch, Jens Grabowski:
A systematic mapping study of developer social network research. J. Syst. Softw. 171: 110802 (2021) - [j20]Steffen Herbold:
On the Costs and Profit of Software Defect Prediction. IEEE Trans. Software Eng. 47(11): 2617-2631 (2021) - [c26]Steffen Herbold:
On the Cost and Profit of Software Defect Prediction. Software Engineering 2021: 53 - [c25]Steffen Herbold, Alexander Trautsch, Fabian Trautsch:
On the Feasibility of Automated Prediction of Bug and Non-Bug Issues. Software Engineering 2021: 55-56 - [c24]Steffen Herbold, Aynur Amirfallah, Fabian Trautsch, Jens Grabowski:
A Systematic Mapping Study of Developer Social Network Research. Software Engineering 2021: 57-58 - [c23]Alexander Trautsch, Steffen Herbold, Jens Grabowski:
A Longitudinal Study of Static Analysis Warning Evolution and the Effects of PMD on Software Quality in Apache Open Source Projects. Software Engineering 2021: 107-108 - [c22]Fabian Trautsch, Steffen Herbold, Jens Grabowski:
Are Unit and Integration Test Definitions Still Valid for Modern Java Projects? An Empirical Study on Open-Source Projects. Software Engineering 2021: 109-110 - [d7]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.1 Full. 1.0. GRO.data, 2021 [all versions] - [d6]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.1 Full. 1.1. GRO.data, 2021 [all versions] - [d5]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 1.3. 1.1. GRO.data, 2021 [all versions] - [d4]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.2 Full. 1.0. GRO.data, 2021 [all versions] - [d3]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.2 Small. 1.0. GRO.data, 2021 [all versions] - [d2]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.1 Small. GRO.data, 2021 - [d1]Alexander Trautsch, Fabian Trautsch, Steffen Herbold:
SmartSHARK 2.1 Small. GRO.data, 2021 - [i23]Alexander Trautsch, Steffen Herbold:
The SmartSHARK Repository Mining Data. CoRR abs/2102.11540 (2021) - [i22]Armin Goudarzi, Carsten Spehr, Steffen Herbold:
Expert decision support system for aeroacoustic classification. CoRR abs/2103.00255 (2021) - [i21]Steffen Herbold:
Exploring the relationship between performance metrics and cost saving potential of defect prediction models. CoRR abs/2104.00566 (2021) - [i20]Eike Stein, Steffen Herbold, Fabian Trautsch, Jens Grabowski:
A new perspective on the competent programmer hypothesis through the reproduction of bugs with repeated mutations. CoRR abs/2104.02517 (2021) - [i19]Alexander Trautsch, Johannes Erbel, Steffen Herbold, Jens Grabowski:
On the differences between quality increasing and other changes in open source Java projects. CoRR abs/2109.03544 (2021) - [i18]Julian von der Mosel, Alexander Trautsch, Steffen Herbold:
On the validity of pre-trained transformers for natural language processing in the software engineering domain. CoRR abs/2109.04738 (2021) - [i17]Benjamin Ledel, Steffen Herbold:
Broccoli: Bug localization with the help of text search engines. CoRR abs/2109.11902 (2021) - [i16]Alexander Trautsch, Steffen Herbold, Jens Grabowski:
Are automated static analysis tools worth it? An investigation into relative warning density and external software quality. CoRR abs/2111.09188 (2021) - 2020
- [j19]Alexander Trautsch, Steffen Herbold, Jens Grabowski:
A longitudinal study of static analysis warning evolution and the effects of PMD on software quality in Apache open source projects. Empir. Softw. Eng. 25(6): 5137-5192 (2020) - [j18]Steffen Herbold, Alexander Trautsch, Fabian Trautsch:
On the feasibility of automated prediction of bug and non-bug issues. Empir. Softw. Eng. 25(6): 5333-5369 (2020) - [j17]Steffen Herbold, Alexander Trautsch, Fabian Trautsch:
Correction to: On the feasibility of automated prediction of bug and non-bug issues. Empir. Softw. Eng. 25(6): 5370-5373 (2020) - [j16]Tobias Baum, Steffen Herbold, Kurt Schneider:
GIMO: A multi-objective anytime rule mining system to ease iterative feedback from domain experts. Expert Syst. Appl. X 8: 100040 (2020) - [j15]Steffen Herbold:
Autorank: A Python package for automated ranking of classifiers. J. Open Source Softw. 5(48): 2173 (2020) - [j14]Fabian Trautsch, Steffen Herbold, Jens Grabowski:
Are unit and integration test definitions still valid for modern Java projects? An empirical study on open-source projects. J. Syst. Softw. 159 (2020) - [c21]Alexander Trautsch, Fabian Trautsch, Steffen Herbold, Benjamin Ledel, Jens Grabowski:
The SmartSHARK ecosystem for software repository mining. ICSE (Companion Volume) 2020: 25-28 - [c20]Steffen Herbold:
With registered reports towards large scale data curation. ICSE (NIER) 2020: 93-96 - [c19]Alexander Trautsch, Steffen Herbold, Jens Grabowski:
Static source code metrics and static analysis warnings for fine-grained just-in-time defect prediction. ICSME 2020: 127-138 - [c18]Steffen Herbold, Alexander Trautsch, Benjamin Ledel:
Large-Scale Manual Validation of Bugfixing Changes. MSR 2020: 611-614 - [i15]Alexander Trautsch, Fabian Trautsch, Steffen Herbold, Benjamin Ledel, Jens Grabowski:
The SmartSHARK Ecosystem for Software Repository Mining. CoRR abs/2001.01606 (2020) - [i14]Steffen Herbold:
With Registered Reports Towards Large Scale Data Curation. CoRR abs/2001.01972 (2020) - [i13]Steffen Herbold, Alexander Trautsch, Fabian Trautsch:
On the Feasibility of Automated Issue Type Prediction. CoRR abs/2003.05357 (2020) - [i12]Steffen Herbold, Tobias Haar:
Smoke Testing for Machine Learning: Simple Tests to Discover Severe Defects. CoRR abs/2009.01521 (2020) - [i11]Steffen Herbold, Alexander Trautsch, Benjamin Ledel, Alireza Aghamohammadi, Taher Ahmed Ghaleb, Kuljit Kaur Chahal, Tim Bossenmaier, Bhaveet Nagaria, Philip Makedonski, Matin Nili Ahmadabadi, Kristóf Szabados, Helge Spieker, Matej Madeja, Nathaniel Hoy, Valentina Lenarduzzi, Shangwen Wang, Gema Rodríguez-Pérez, Ricardo Colomo Palacios, Roberto Verdecchia, Paramvir Singh, Yihao Qin, Debasish Chakroborti, Willard Davis, Vijay Walunj, Hongjun Wu, Diego Marcilio, Omar Alam, Abdullah Aldaeej, Idan Amit, Burak Turhan, Simon Eismann, Anna-Katharina Wickert, Ivano Malavolta, Matús Sulír, Fatemeh H. Fard, Austin Z. Henley, Stratos Kourtzanidis, Eray Tuzun, Christoph Treude, Simin Maleki Shamasbi, Ivan Pashchenko, Marvin Wyrich, James Davis, Alexander Serebrenik, Ella Albrecht, Ethem Utku Aktas, Daniel Strüber, Johannes Erbel:
Large-Scale Manual Validation of Bug Fixing Commits: A Fine-grained Analysis of Tangling. CoRR abs/2011.06244 (2020) - [i10]Armin Goudarzi, Carsten Spehr, Steffen Herbold:
Automatic source localization and spectra generation from deconvolved beamforming maps. CoRR abs/2012.09643 (2020)
2010 – 2019
- 2019
- [j13]Steffen Herbold, Fabian Trautsch, Patrick Harms, Verena Herbold, Jens Grabowski:
Chapter Seven - Experiences With Replicable Experiments and Replication Kits for Software Engineering Research. Adv. Comput. 113: 315-344 (2019) - [j12]Steffen Herbold, Alexander Trautsch, Jens Grabowski:
Correction of "A Comparative Study to Benchmark Cross-Project Defect Prediction Approaches". IEEE Trans. Software Eng. 45(6): 632-636 (2019) - [i9]Aynur Amirfallah, Fabian Trautsch, Jens Grabowski, Steffen Herbold:
A systematic mapping study of developer social network research. CoRR abs/1902.07499 (2019) - [i8]Steffen Herbold:
On the costs and profit of software defect prediction. CoRR abs/1911.04309 (2019) - [i7]Steffen Herbold, Alexander Trautsch, Fabian Trautsch:
Issues with SZZ: An empirical assessment of the state of practice of defect prediction data collection. CoRR abs/1911.08938 (2019) - [i6]Alexander Trautsch, Steffen Herbold, Jens Grabowski:
A Longitudinal Study of Static Analysis Warning Evolution and the Effects of PMD on Software Quality in Apache Open Source Projects. CoRR abs/1912.02179 (2019) - 2018
- [j11]Fabian Trautsch, Steffen Herbold, Philip Makedonski, Jens Grabowski:
Addressing problems with replicability and validity of repository mining studies through a smart data platform. Empir. Softw. Eng. 23(2): 1036-1083 (2018) - [j10]Steffen Herbold, Alexander Trautsch, Jens Grabowski:
A Comparative Study to Benchmark Cross-Project Defect Prediction Approaches. IEEE Trans. Software Eng. 44(9): 811-833 (2018) - [c17]Steffen Herbold, Alexander Trautsch, Jens Grabowski:
A comparative study to benchmark cross-project defect prediction approaches. ICSE 2018: 1063 - [i5]Steffen Herbold:
Benchmarking cross-project defect prediction approaches with costs metrics. CoRR abs/1801.04107 (2018) - [i4]Tobias Baum, Steffen Herbold, Kurt Schneider:
An Industrial Case Study on Shrinking Code Review Changesets through Remark Prediction. CoRR abs/1812.09510 (2018) - [i3]Tobias Baum, Steffen Herbold, Kurt Schneider:
A Multi-Objective Anytime Rule Mining System to Ease Iterative Feedback from Domain Experts. CoRR abs/1812.09746 (2018) - 2017
- [j9]Steffen Herbold, Alexander Trautsch, Jens Grabowski:
Global vs. local models for cross-project defect prediction - A replication study. Empir. Softw. Eng. 22(4): 1866-1902 (2017) - [j8]Steffen Herbold, Andreas Hoffmann:
Model-based testing as a service. Int. J. Softw. Tools Technol. Transf. 19(3): 271-279 (2017) - [j7]Steffen Herbold, Patrick Harms, Jens Grabowski:
Combining usage-based and model-based testing for service-oriented architectures in the industrial practice. Int. J. Softw. Tools Technol. Transf. 19(3): 309-324 (2017) - [j6]Steffen Herbold:
Comments on ScottKnottESD in Response to "An Empirical Comparison of Model Validation Techniques for Defect Prediction Models". IEEE Trans. Software Eng. 43(11): 1091-1094 (2017) - [c16]Xiaowei Wang, Fabian Glaser, Steffen Herbold, Jens Grabowski:
On the Relatively Small Impact of Deep Dependencies on Cloud Application Reliability. CLOUD 2017: 528-535 - [c15]Harald Altinger, Steffen Herbold, Friederike Schneemann, Jens Grabowski, Franz Wotawa:
Performance tuning for automotive Software Fault Prediction. SANER 2017: 526-530 - [i2]Steffen Herbold:
A systematic mapping study on cross-project defect prediction. CoRR abs/1705.06429 (2017) - [i1]Steffen Herbold, Alexander Trautsch, Jens Grabowski:
Correction of "A Comparative Study to Benchmark Cross-project Defect Prediction Approaches". CoRR abs/1707.09281 (2017) - 2016
- [c14]Fabian Trautsch, Steffen Herbold, Philip Makedonski, Jens Grabowski:
Adressing problems with external validity of repository mining studies through a smart data platform. MSR 2016: 97-108 - [c13]Verena Honsel, Steffen Herbold, Jens Grabowski:
Learning from Software Project Histories - Predictive Studies Based on Mining Software Repositories. ECML/PKDD (3) 2016: 267-270 - [c12]Verena Honsel, Steffen Herbold, Jens Grabowski:
Hidden Markov Models for the Prediction of Developer Involvement Dynamics and Workload. PROMISE 2016: 8:1-8:10 - [e1]Jens Grabowski, Steffen Herbold:
System Analysis and Modeling. Technology-Specific Aspects of Models - 9th International Conference, SAM 2016, Saint-Melo, France, October 3-4, 2016, Proceedings. Lecture Notes in Computer Science 9959, Springer 2016, ISBN 978-3-319-46612-5 [contents] - 2015
- [j5]Martin A. Schneider, Steffen Herbold:
Effizientere IT-Sicherheitstest mit Hilfe von Usagebased Testing. Softwaretechnik-Trends 35(1) (2015) - [c11]Steffen Herbold, Alberto De Francesco, Jens Grabowski, Patrick Harms, Lom-Messan Hillah, Fabrice Kordon, Ariele-Paolo Maesano, Libero Maesano, Claudia Di Napoli, Fabio De Rosa, Martin A. Schneider, Nicola Tonellotto, Marc-Florian Wendland, Pierre-Henri Wuillemin:
The MIDAS Cloud Platform for Testing SOA Applications. ICST 2015: 1-8 - [c10]Steffen Herbold:
CrossPare: A Tool for Benchmarking Cross-Project Defect Predictions. ASE Workshops 2015: 90-96 - [c9]Verena Honsel, Daniel Honsel, Steffen Herbold, Jens Grabowski, Stephan Waack:
Mining Software Dependency Networks for Agent-Based Simulation of Software Evolution. ASE Workshops 2015: 102-108 - [c8]Verena Honsel, Steffen Herbold, Jens Grabowski:
Intuition vs. Truth: Evaluation of Common Myths about StackOverflow Posts. MSR 2015: 438-441 - [c7]Harald Altinger, Steffen Herbold, Jens Grabowski, Franz Wotawa:
Novel Insights on Cross Project Fault Prediction Applied to Automotive Software. ICTSS 2015: 141-157 - [c6]Martin A. Schneider, Steffen Herbold, Marc-Florian Wendland, Jens Grabowski:
Improving Security Testing with Usage-Based Fuzz Testing. RISK 2015: 110-119 - [c5]Michael Göttsche, Fabian Glaser, Steffen Herbold, Jens Grabowski:
Automated Deployment and Parallel Execution of Legacy Applications in Cloud Environments (Short Paper). SOCA 2015: 188-192 - 2014
- [j4]Thomas Brodag, Steffen Herbold, Stephan Waack:
A Generalized Model of PAC Learning and its Applicability. RAIRO Theor. Informatics Appl. 48(2): 209-245 (2014) - 2013
- [c4]Steffen Herbold, Patrick Harms:
AutoQUEST - Automated Quality Engineering of Event-Driven Software. ICST Workshops 2013: 134-139 - [c3]Steffen Herbold:
Training data selection for cross-project defect prediction. PROMISE 2013: 6:1-6:10 - 2012
- [b1]Steffen Herbold:
Usage-based Testing of Event-driven Software. University of Göttingen, 2012 - [j3]Steffen Herbold, Uwe Bünting, Jens Grabowski, Stephan Waack:
Deployable Capture/Replay Supported by Internal Messages. Adv. Comput. 85: 327-367 (2012) - 2011
- [j2]Steffen Herbold, Jens Grabowski, Stephan Waack:
Calculation and optimization of thresholds for sets of software metrics. Empir. Softw. Eng. 16(6): 812-841 (2011) - [c2]Steffen Herbold, Jens Grabowski, Stephan Waack, Uwe Bünting:
Improved Bug Reporting and Reproduction through Non-intrusive GUI Usage Monitoring and Automated Replaying. ICST Workshops 2011: 232-241 - [c1]Steffen Herbold, Jens Grabowski, Stephan Waack:
A Model for Usage-Based Testing of Event-Driven Software. SSIRI (Companion) 2011: 172-178 - 2010
- [j1]Steffen Herbold, Jens Grabowski, Helmut Neukirchen, Stephan Waack:
Retrospective Analysis of Software Projects using k-Means Clustering. Softwaretechnik-Trends 30(2) (2010)
Coauthor Index
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