Supervision
This course is supervised by Raphael Dunkel and Thomas Thüm.
Topics
The Dynamics of Decentralized Versus Centralized Development and Version Management
- Kıvanç Muşlu, Christian Bird, Nachiappan Nagappan, and Jacek Czerwonka. 2014. Transition from centralized to decentralized version control systems: a case study on reasons, barriers, and outcomes. In Proceedings of the 36th International Conference on Software Engineering (ICSE 2014). Association for Computing Machinery, New York, NY, USA, 334–344. https://doi.org/10.1145/2568225.2568284
- Singh, V., Aggarwal, A. (2024). Limitations of Centralized Version Control Systems (SVN) and Approaches to Its Migration to Decentralized VCS. In: Bhardwaj, A., Pandey, P.M., Misra, A. (eds) Optimization of Production and Industrial Systems. CPIE 2023. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-8343-8_10
- C. Rodríguez-Bustos and J. Aponte, "How Distributed Version Control Systems impact open source software projects," 2012 9th IEEE Working Conference on Mining Software Repositories (MSR), Zurich, Switzerland, 2012, pp. 36-39, https://doi.org/10.1109/MSR.2012.6224297
AI in Open-Source Development Onboarding
- Felipe Fronchetti, David C. Shepherd, Igor Wiese, Christoph Treude, Marco Aurélio Gerosa, and Igor Steinmacher. “Do CONTRIBUTING Files Provide Information about OSS Newcomers’ Onboarding Barriers?” In: Proc. Int’l Symposium on Foundations of Software Engineering (FSE). ACM, 2023, 16–28. doi: 10.1145/3611643.3616288.
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Ítalo Santos, Kátia Romero Felizardo, Igor Steinmacher, and Marco Aurélio Gerosa. “Software Solutions for Newcomers’ Onboarding in Software Projects: A Systematic Literature Review”. In: J. Information and Software Technology (IST) 177 (2025), p. 107568. doi: 10.1016/J.INFSOF.2024.107568.
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Xin Tan, Xiao Long, Yinghao Zhu, Lin Shi, Xiaoli Lian, and Li Zhang. “Revolutionizing Newcomers’ Onboarding Process in OSS Communities: The Future AI Mentor”. In: Proc. Int’l Symposium on Foundations of Software Engineering (FSE) 2 (2025). doi: 10.1145/3715767.
The Social and Technical Implications of Branches Versus Forks
- Shurui Zhou, Bogdan Vasilescu, and Christian Kästner. 2019. What the fork: a study of inefficient and efficient forking practices in social coding. In Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2019). Association for Computing Machinery, New York, NY, USA, 350–361. https://doi.org/10.1145/3338906.3338918
- Robles, G., González-Barahona, J.M. (2012). A Comprehensive Study of Software Forks: Dates, Reasons and Outcomes. In: Hammouda, I., Lundell, B., Mikkonen, T., Scacchi, W. (eds) Open Source Systems: Long-Term Sustainability. OSS 2012. IFIP Advances in Information and Communication Technology, vol 378. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33442-9_1
- Christian Bird and Thomas Zimmermann. 2012. Assessing the value of branches with what-if analysis. In Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering (FSE '12). Association for Computing Machinery, New York, NY, USA, Article 45, 1–11. https://doi.org/10.1145/2393596.2393648
The Role and Effectiveness of Pull-Requests in Collaborative Workflows
- D. Ford, M. Behroozi, A. Serebrenik and C. Parnin, "Beyond the Code Itself: How Programmers Really Look at Pull Requests," 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS), Montreal, QC, Canada, 2019, pp. 51-60, https://doi.org/10.1109/ICSE-SEIS.2019.00014
- Moreira Soares D, de Lima Júnior ML, Murta L, Plastino A. What factors influence the lifetime of pull requests?. Softw Pract Exper. 2021; 51: 1173–1193. https://doi.org/10.1002/spe.2946
- Chandra Maddila, Sai Surya Upadrasta, Chetan Bansal, Nachiappan Nagappan, Georgios Gousios, and Arie van Deursen. 2023. Nudge: Accelerating Overdue Pull Requests toward Completion. ACM Trans. Softw. Eng. Methodol. 32, 2, Article 35 (March 2023), 30 pages. https://doi.org/10.1145/3544791
The Differences Between Structured, Semi-Structured, and Unstructured Merging Techniques
- T. Mens, "A state-of-the-art survey on software merging," in IEEE Transactions on Software Engineering, vol. 28, no. 5, pp. 449-462, May 2002, https://doi.org/10.1109/TSE.2002.1000449
- G. Cavalcanti, P. Borba, G. Seibt and S. Apel, "The Impact of Structure on Software Merging: Semistructured Versus Structured Merge," 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE), San Diego, CA, USA, 2019, pp. 1002-1013, https://doi.org/10.1109/ASE.2019.00097
- Guilherme Cavalcanti, Paulo Borba, and Paola Accioly. 2017. Evaluating and improving semistructured merge. Proc. ACM Program. Lang. 1, OOPSLA, Article 59 (October 2017), 27 pages. https://doi.org/10.1145/3133883
AI-based Code Explanation in Code Reviews
- Lo Heander, Emma Söderberg, and Christofer Rydenfält. “Support, Not Automation: Towards AI-supported Code Review For Code Quality and Beyond”. In: Proc. Int’l Symposium on Foundations of Software Engineering (FSE). ACM, 2025, 591–595. doi: 10.1145/3696630.3728505.
- Juho Leinonen, Paul Denny, Stephen MacNeil, Sami Sarsa, Seth Bernstein, Joanne Kim, Andrew Tran, and Arto Hellas. “Comparing Code Explanations Created by Students and Large Language Models”. In: Proc. Conf. on Innovation and Technology in Computer Science Education (ITiCSE). ACM, 2023, 124–130. doi: 10.1145/3587102.3588785.
- Daye Nam, Andrew Macvean, Vincent Hellendoorn, Bogdan Vasilescu, and Brad Myers. “Using an LLM to Help With Code Understanding”. In: Proc. Int’l Conf. on Software Engineering (ICSE). ACM, 2024. doi: 10.1145/3597503.3639187.
Maintenance of Software Forks
- J. Businge, M. Openja, S. Nadi, E. Bainomugisha and T. Berger, "Clone-Based Variability Management in the Android Ecosystem," 2018 IEEE International Conference on Software Maintenance and Evolution (ICSME), Madrid, Spain, 2018, pp. 625-634, https://doi.org/10.1109/ICSME.2018.00072
- Poedjadevie Kadjel Ramkisoen, John Businge, Brent van Bladel, Alexandre Decan, Serge Demeyer, Coen De Roover, and Foutse Khomh. 2022. PaReco: patched clones and missed patches among the divergent variants of a software family. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2022). Association for Computing Machinery, New York, NY, USA, 646–658. https://doi.org/10.1145/3540250.3549112
- Panuchart Bunyakiati and Chadarat Phipathananunth. 2017. Cherry-picking of code commits in long-running, multi-release software. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering (ESEC/FSE 2017). Association for Computing Machinery, New York, NY, USA, 994–998. https://doi.org/10.1145/3106237.3122818
Software Composition Analysis and its Importance for Software Security
- Zerouali, A., Mens, T., Decan, A. et al. On the impact of security vulnerabilities in the npm and RubyGems dependency networks. Empir Software Eng 27, 107 (2022). https://doi.org/10.1007/s10664-022-10154-1
- Nasif Imtiaz, Seaver Thorn, and Laurie Williams. 2021. A comparative study of vulnerability reporting by software composition analysis tools. In Proceedings of the 15th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) (ESEM '21). Association for Computing Machinery, New York, NY, USA, Article 5, 1–11. https://doi.org/10.1145/3475716.3475769
- Laura Bottner, Artur Hermann, Jeremias Eppler, Thomas Thüm, and Frank Kargl. 2023. Evaluation of Free and Open Source Tools for Automated Software Composition Analysis. In Proceedings of the 7th ACM Computer Science in Cars Symposium (CSCS '23). Association for Computing Machinery, New York, NY, USA, Article 3, 1–11. https://doi.org/10.1145/3631204.3631862
Existing Practices for Commenting and Documentation of Software Projects
- Rani, P., Panichella, S., Leuenberger, M. et al. What do class comments tell us? An investigation of comment evolution and practices in Pharo Smalltalk. Empir Software Eng 26, 112 (2021). https://doi.org/10.1007/s10664-021-09981-5
- Emad Aghajani, Csaba Nagy, Mario Linares-Vásquez, Laura Moreno, Gabriele Bavota, Michele Lanza, and David C. Shepherd. 2020. Software documentation: the practitioners' perspective. In Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering (ICSE '20). Association for Computing Machinery, New York, NY, USA, 590–601. https://doi.org/10.1145/3377811.3380405
- Chao Wang, Hao He, Uma Pal, Darko Marinov, and Minghui Zhou. 2023. Suboptimal Comments in Java Projects: From Independent Comment Changes to Commenting Practices. ACM Trans. Softw. Eng. Methodol. 32, 2, Article 45 (March 2023), 33 pages. https://doi.org/10.1145/3546949
Automated Sentiment Analysis in Software Teams
- Marc Herrmann, Martin Obaidi, Larissa Chazette, and Jil Klünder. “On the Subjectivity of Emotions in Software Projects: How Reliable Are Pre-Labeled Data Sets for Sentiment Analysis?” In: J. Systems and Software (JSS) 193.C (2022). doi: 10.1016/j.jss.2022.111448.
- Bin Lin, Fiorella Zampetti, Gabriele Bavota, Massimiliano Di Penta, Michele Lanza, and Rocco Oliveto. “Sentiment Analysis for Software Engineering: How Far Can We Go?” In: Proc. Int’l Conf. on Software Engineering (ICSE). ACM, 2018, 94–104. doi: 10.1145/3180155.3180195.
- Ting Zhang, Bowen Xu, Ferdian Thung, Stefanus Agus Haryono, David Lo, and Lingxiao Jiang. “Sentiment Analysis for Software Engineering: How Far Can Pre-trained Transformer Models Go?” In: Proc. Int’l Conf. on Software Maintenance and Evolution (ICSME). IEEE, 2020, pp. 70–80. doi: 10.1109/ICSME46990.2020.00017.
Continuous Integration, Delivery, and Deployment in Collaborative Software Development
- Michael Hilton, Timothy Tunnell, Kai Huang, Darko Marinov, and Danny Dig. 2016. Usage, costs, and benefits of continuous integration in open-source projects. In Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering (ASE '16). Association for Computing Machinery, New York, NY, USA, 426–437. https://doi.org/10.1145/2970276.2970358
- Mojtaba Shahin, Mansooreh Zahedi, Muhammad Ali Babar, and Liming Zhu. 2017. Adopting Continuous Delivery and Deployment: Impacts on Team Structures, Collaboration and Responsibilities. In Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering (EASE '17). Association for Computing Machinery, New York, NY, USA, 384–393. https://doi.org/10.1145/3084226.3084263
- R. K. Gupta, M. Venkatachalapathy and F. K. Jeberla, "Challenges in Adopting Continuous Delivery and DevOps in a Globally Distributed Product Team: A Case Study of a Healthcare Organization," 2019 ACM/IEEE 14th International Conference on Global Software Engineering (ICGSE), Montreal, QC, Canada, 2019, pp. 30-34, https://doi.org/10.1109/ICGSE.2019.00020
Impact of AI on Teaching Programming to Students
- Tran Tri Dang, Huo-Chong Ling, and Ngoc Quang Tran. “Combating ChatGPT-Based Programming Test Cheating — An Evaluation Using Public Problems”. In: Proc. Int’l Conf. on Computer Science and Technologies in Education (CSTE). IEEE, 2024, pp. 161–165. doi: 10.1109/CSTE62025.2024.00037.
- Christian Rahe and Walid Maalej. “How Do Programming Students Use Generative AI?” In: Proc. Int’l Symposium on Foundations of Software Engineering (FSE) 2 (2025). doi: 10.1145/3715762.
- Yi-Miao Yan, Chuang-Qi Chen, Yang-Bang Hu, and Xin-Dong Ye. “LLM-Based Collaborative Programming: Impact on Students’ Computational Thinking and Self-Efficacy”. In: J. Humanities and Social Sciences Communications 12.1 (2025), p. 149. doi: 10.1057/s41599-025-04471-1.
(Automated) Team Recommendation for Collaborative Software Development
- Tuarob, S., Assavakamhaenghan, N., Tanaphantaruk, W. et al. Automatic team recommendation for collaborative software development. Empir Software Eng 26, 64 (2021). https://doi.org/10.1007/s10664-021-09966-4
- Assavakamhaenghan, N., Tanaphantaruk, W., Suwanworaboon, P. et al. Quantifying effectiveness of team recommendation for collaborative software development. Autom Softw Eng 29, 51 (2022). https://doi.org/10.1007/s10515-022-00357-7
- Pisol Ruenin, Morakot Choetkiertikul, Akara Supratak, Suppawong Tuarob, TeReKG: A temporal collaborative knowledge graph framework for software team recommendation, Knowledge-Based Systems, Volume 289, 2024, 111492, ISSN 0950-7051, https://doi.org/10.1016/j.knosys.2024.111492
AI as a Partner in Pair Programming
- Jiangyue Liu and Siran Li. “Toward Artificial Intelligence-Human Paired Programming: A Review of the Educational Applications and Research on Artificial Intelligence Code-Generation Tools”. In: J. Educational Computing Research 62.5 (2024), pp. 1165–1195. doi: 10.1177/07356331241240460.
- Nathalia Nascimento, Paulo Alencar, and Donald Cowan. “Artificial Intelligence vs. Software Engineers: An Empirical Study on Performance and Efficiency using ChatGPT”. In: Proc. Conf. Centre for Advanced Studies on Collaborative Research (CASCON). IBM Corp., 2023, 24–33. doi: 10.5555/3615924.3615927.
- Alisa Carla Welter, Niklas Schneider, Tobias Dick, Kallistos Weis, Christof Tinnes, Marvin Wyrich, and Sven Apel. “An Empirical Study of Knowledge Transfer in AI Pair Programming”. In: Proc. Int’l Conf. on Automated Software Engineering (ASE). To appear. ACM, 2025.
Material
The course material is provided in the corresponding Stud.IP course.
