Potential Topics

Summarization:
StackOverFlow Post
1.	Kou, Bonan, et al. "Automated Summarization of Stack Overflow Posts." ICSE, 2023.
2.	Yang, Chengran, et al. "Answer Summarization for Technical Queries: Benchmark and New Approach." 37th IEEE/ACM International Conference on Automated Software Engineering (ASE). 2022.
Bug Report Summarization
1.	Liu, Haoran, et al. "Bugsum: Deep context understanding for bug report summarization." Proceedings of the 28th International Conference on Program Comprehension (ICPC). 2020.
2.	Hao, Rui, et al. "Are duplicates really harmful? An empirical study on bug report summarization techniques." Journal of Software: Evolution and Process (2022).
3.	Senthil Mani, Rose Catherine, Vibha Singhal Sinha, and Avinava Dubey. 2012. Ausum: approach for unsupervised bug report summarization. In Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering. ACM, 11
	Title Generation
1.	Irsan, Ivana Clairine, et al. "AutoPRTitle: A Tool for Automatic Pull Request Title Generation." 2022 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 2022.
2.	T.Zhang,I.C.Irsan,F.Thung,D.Han,D.Lo,andL.Jiang,“Automatic pull request title generation,” 2022 IEEE 38th International Conference on Software Maintenance and Evolution (ICSME), Research Track.
3.	Z. Gao, X. Xia, D. Lo, J. Grundy, and Y.-F. Li, “Code2Que: a tool for improving question titles from mined code snippets in stack overflow,” in Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2021, pp. 1525–1529.
4.	S. Chen, X. Xie, B. Yin, Y. Ji, L. Chen, and B. Xu, “Stay professional and efficient: Automatically generate titles for your bug reports,” in 2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 2020, pp. 385–397.
Software-related Document Classification
Issue/Bug Reports
1.	Kallis, Rafael, et al. "Ticket tagger: Machine learning driven issue classification." 2019 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 2019.
2.	Fan, Qiang, et al. "Where is the road for issue reports classification based on text mining?." 2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE, 2017.
3.	Zheng, Wei, et al. "A comparative study of class rebalancing methods for security bug report classification." IEEE Transactions on Reliability 70.4 (2021): 1658-1670.
4.	Wu, Xiaoxue, et al. "Data quality matters: A case study on data label correctness for security bug report prediction." IEEE Transactions on Software Engineering 48.7 (2021): 2541-2556.
Code Review
1.	Baum, Tobias, et al. "A faceted classification scheme for change-based industrial code review processes." 2016 IEEE International conference on software quality, reliability and security (QRS). IEEE, 2016.
2.	Fregnan, Enrico, et al. "What happens in my code reviews? An investigation on automatically classifying review changes." Empirical Software Engineering 27.4 (2022): 89.

	API Review
1.	Yang, Chengran, et al. "Aspect-Based API Review Classification: How Far Can Pre-Trained Transformer Model Go?." 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). IEEE, 2022.
2.	G. Uddin and F. Khomh, “Automatic mining of opinions expressed about apis in stack overflow,” IEEE Transactions on Software Engineer- ing, vol. 47, no. 3, pp. 522–559, 2021.
3.	G. Uddin and F. Khomh, “Mining api aspects in api reviews,” in Technical Report, 2017.
Recommendation for Software Artifacts
Topic/Tags
1.	He, Junda, et al. "PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models." Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension. 2022.
2.	Di Rocco, Juri, et al. "Topfilter: an approach to recommend relevant github topics." Proceedings of the 14th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). 2020.
3.	Shaowei Wang, David Lo, Bogdan Vasilescu, and Alexander Serebrenik. 2014. EnTagRec: An Enhanced Tag Recommendation System for Software Information Sites. In 2014 IEEE International Conference on Software Maintenance and Evolution. 291–300. 
4.	Shaowei Wang, David Lo, Bogdan Vasilescu, and Alexander Serebrenik. 2018. EnTagRec ++: An enhanced tag recommendation system for software information sites. Empirical Software Engineering 23 (04 2018).
5.	Ratna et al “Topic Recommendation for GitHub Repositories: How Far Can Extreme Multi-Label Learning Go” SANER 2023

API
1.	Y. Zhou, X. Yang, T. Chen, Z. Huang, X. Ma, and H. Gall, “Boosting api recommendation with implicit feedback,” IEEE Transactions on Software Engineering, vol. 48, no. 6, pp. 2157–2172, 2021.
2.	Ivana et al. “PICASO: Enhancing API Recommendations with Relevant Stack Overflow Posts”
3.	Wei, Moshi, et al. "Clear: contrastive learning for api recommendation." Proceedings of the 44th International Conference on Software Engineering. 2022.
Information Recognition/Identification
Vulnerability-Affected Library Identification  
1.	Lyu, Yunbo, et al. "CHRONOS: Time-Aware Zero-Shot Identification of Libraries from Vulnerability Reports." ICSE 23
2.	S. A. Haryono, H. J. Kang, A. Sharma, A. Sharma, A. Santosa, A. M. Yi, and D. Lo, “Automated identification of libraries from vulnerability data: can we do better?” in IEEE/ACM International Conference on Program Comprehension (ICPC), 2022.
3.	Y. Chen, A. E. Santosa, A. Sharma, and D. Lo, “Automated identification of libraries from vulnerability data,” in Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Software En- gineering in Practice (ICSE-SEIP), 2020, pp. 90–99.

Library Recognition in Tweets 
1.	Zhang, Ting, et al. "Benchmarking library recognition in tweets." Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension. 2022.
	Informative Code in StackOverFLow Posts 
1.	Chatterjee, Preetha. "Automatic identification of informative code in stack overflow posts." 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE). IEEE, 2022.
Duplication Detection for Software Artifacts
	Bug Reports
1.	Zhang, Ting, et al. "Duplicate Bug Report Detection: How Far Are We?." ACM Transactions on Software Engineering and Methodology (2022).
2.	Mohamed Sami Rakha, Cor-Paul Bezemer, and Ahmed E Hassan. 2018. Revisiting the performance of automated approaches for the retrieval of duplicate reports in issue tracking systems that perform just-in-time duplicate retrieval. Empirical Software Engineering 23, 5
(2018).
3.	Feifei Tu, Jiaxin Zhu, Qimu Zheng, and Minghui Zhou. 2018. Be Careful of When: An Empirical Study on Time-Related Misuse of Issue Tracking Data. In Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (Lake Buena Vista, FL, USA) (ESEC/FSE 2018).

StackOverFlow Posts
1.	Ahasanuzzaman, Muhammad, et al. "Mining duplicate questions in stack overflow." Proceedings of the 13th International Conference on Mining Software Repositories. 2016.
2.	Baltes, Sebastian, and Christoph Treude. "Code duplication on stack overflow." Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: New Ideas and Emerging Results. 2020.
3.	Abric, Durham, et al. "Can duplicate questions on stack overflow benefit the software development community?." 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR). IEEE, 2019.



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