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ChatGPT has significantly impacted software development practices, providing substantial assistance to developers in a variety of tasks, including coding, testing, and debugging.
Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. biometrics pp 159–174
1977
Earlier work this paper cites.
Treude C, Barzilay O, Storey MA (2011) How do programmers ask and answer questions on the web?(nier track). In: Proceedings of the 33rd international conference on software engineering, pp 804–807
2011
Earlier work this paper cites.
Gómez C, Cleary B, Singer L (2013) A study of innovation diffusion through link sharing on stack overflow. In: 2013 10th working conference on mining software repositories (MSR), IEEE, pp 81–84
2013
Earlier work this paper cites.
Di Sorbo A, Panichella S, Visaggio CA, Di Penta M, Canfora G, Gall HC (2015) Development emails content analyzer: Intention mining in developer discussions (t). In: 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE), IEEE, pp 12–23
2015
Earlier work this paper cites.
Rosen C, Shihab E (2016) What are mobile developers asking about? a large scale study using stack overflow. Empirical Software Engineering 21:1192–1223
2016
Earlier work this paper cites.
Gagniuc PA (2017) Markov chains: from theory to implementation and experimentation. John Wiley & Sons
2017
Earlier work this paper cites.
Ye D, Xing Z, Kapre N (2017) The structure and dynamics of knowledge network in domain-specific q&a sites: a case study of stack overflow. Empirical Software Engineering 22:375–406
2017
Earlier work this paper cites.
Zampetti F, Ponzanelli L, Bavota G, Mocci A, Di Penta M, Lanza M (2017) How developers document pull requests with external references. In: 2017 IEEE/ACM 25th International Conference on Program Comprehension (ICPC), IEEE, pp 23–33
2017
Earlier work this paper cites.
Huang Q, Xia X, Lo D, Murphy GC (2018) Automating intention mining. IEEE Transactions on Software Engineering 46(10):1098–1119
2018
Earlier work this paper cites.
Li L, Ren Z, Li X, Zou W, Jiang H (2018) How are issue units linked? empirical study on the linking behavior in github. In: 2018 25th Asia-Pacific Software Engineering Conference (APSEC), IEEE, pp 386–395
2018
Earlier work this paper cites.
Zhang Y, Yu Y, Wang H, Vasilescu B, Filkov V (2018) Within-ecosystem issue linking: a large-scale study of rails. In: Proceedings of the 7th international workshop on software mining, pp 12–19
2018
Earlier work this paper cites.
Arya D, Wang W, Guo JL, Cheng J (2019) Analysis and detection of information types of open source software issue discussions. In: 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE), IEEE, pp 454–464
2019
Earlier work this paper cites.
Hata H, Treude C, Kula RG, Ishio T (2019) 9.6 million links in source code comments: Purpose, evolution, and decay. In: 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE), IEEE, pp 1211–1221
2019
Earlier work this paper cites.
Qu C, Yang L, Croft WB, Zhang Y, Trippas JR, Qiu M (2019) User intent prediction in information-seeking conversations. In: Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, pp 25–33
2019
Earlier work this paper cites.
Viviani G, Famelis M, Xia X, Janik-Jones C, Murphy GC (2019) Locating latent design information in developer discussions: A study on pull requests. IEEE Transactions on Software Engineering 47(7):1402–1413
2019
Earlier work this paper cites.
Wan Z, Xia X, Hassan AE (2019) What is discussed about blockchain? a case study on the use of balanced lda and the reference architecture of a domain to capture online discussions about blockchain platforms across the stack exchange communities. IEEE Transactions on Software Engineering (01):1–1
2019
Cited alongside, same era.
Zhang T, Gao C, Ma L, Lyu M, Kim M (2019) An empirical study of common challenges in developing deep learning applications. In: 2019 IEEE 30th International Symposium on Software Reliability Engineering (ISSRE), IEEE, pp 104–115
2019
Cited alongside, same era.
Baltes S, Treude C, Robillard MP (2020) Contextual documentation referencing on stack overflow. IEEE Transactions on Software Engineering 48(1):135–149
2020
Cited alongside, same era.
Beyer S, Macho C, Di Penta M, Pinzger M (2020) What kind of questions do developers ask on stack overflow? a comparison of automated approaches to classify posts into question categories. Empirical Software Engineering 25:2258–2301
Barke S, James MB, Polikarpova N (2023) Grounded copilot: How programmers interact with code-generating models. Proceedings of the ACM on Programming Languages 7(OOPSLA1):85–111
2023
Later among the works it cites.
Hou X, Zhao Y, Liu Y, Yang Z, Wang K, Li L, Luo X, Lo D, Grundy J, Wang H (2023) Large language models for software engineering: A systematic literature review. arXiv preprint arXiv:230810620
2023
Later among the works it cites.
Jiang N, Liu K, Lutellier T, Tan L (2023) Impact of code language models on automated program repair. In: Proceedings of the 45th International Conference on Software Engineering, IEEE Press, ICSE ’23, p 1430–1442, DOI 10.1109/ICSE48619.2023.00125
2023
Later among the works it cites.
Lu J, Yu L, Li X, Yang L, Zuo C (2023) Llama-reviewer: Advancing code review automation with large language models through parameter-efficient fine-tuning. In: 2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE), IEEE, pp 647–658
2023
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2020
Cited alongside, same era.
Chen M, Tworek J, Jun H, Yuan Q, Pinto HPdO, Kaplan J, Edwards H, Burda Y, Joseph N, Brockman G, et al. (2021) Evaluating large language models trained on code. arXiv preprint arXiv:210703374
2021
Cited alongside, same era.
Liu J, Xia X, Lo D, Zhang H, Zou Y, Hassan AE, Li S (2021) Broken external links on stack overflow. IEEE Transactions on Software Engineering 48(9):3242–3267
2021
Cited alongside, same era.
Shi L, Chen X, Yang Y, Jiang H, Jiang Z, Niu N, Wang Q (2021) A first look at developers’ live chat on gitter. In: Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp 391–403
2021
Cited alongside, same era.
Wang D, Xiao T, Thongtanunam P, Kula RG, Matsumoto K (2021) Understanding shared links and their intentions to meet information needs in modern code review: A case study of the openstack and qt projects. Empirical Software Engineering 26:1–32
2021
Cited alongside, same era.
Hata H, Novielli N, Baltes S, Kula RG, Treude C (2022) Github discussions: An exploratory study of early adoption. Empirical Software Engineering 27:1–32
2022
Cited alongside, same era.
Liu J, Zhang H, Xia X, Lo D, Zou Y, Hassan AE, Li S (2022) An exploratory study on the repeatedly shared external links on stack overflow. Empirical Software Engineering 27:1–32
2022
Cited alongside, same era.
Mozannar H, Bansal G, Fourney A, Horvitz E (2022) Reading between the lines: Modeling user behavior and costs in ai-assisted programming. arXiv preprint arXiv:221014306
2022
Cited alongside, same era.
Nijkamp E, Pang B, Hayashi H, Tu L, Wang H, Zhou Y, Savarese S, Xiong C (2022) Codegen: An open large language model for code with multi-turn program synthesis. In: The Eleventh International Conference on Learning Representations
2022
Cited alongside, same era.
Later among the works it cites.
Ross SI, Martinez F, Houde S, Muller M, Weisz JD (2023) The programmer’s assistant: Conversational interaction with a large language model for software development. In: Proceedings of the 28th International Conference on Intelligent User Interfaces, pp 491–514
2023
Later among the works it cites.
Siddiq ML, Santos J, Tanvir RH, Ulfat N, Rifat FA, Lopes VC (2023) Exploring the effectiveness of large language models in generating unit tests. arXiv preprint arXiv:230500418
2023
Later among the works it cites.
Xiao T, Baltes S, Hata H, Treude C, Kula RG, Ishio T, Matsumoto K (2023) 18 million links in commit messages: purpose, evolution, and decay. Empirical Software Engineering 28(4):91
2023
Later among the works it cites.
Zhang B, Liang P, Zhou X, Ahmad A, Waseem M (2023) Practices and challenges of using github copilot: An empirical study. arXiv preprint arXiv:230308733
2023
Later among the works it cites.
Deng Y, Xia CS, Yang C, Zhang SD, Yang S, Zhang L (2024) Large language models are edge-case generators: Crafting unusual programs for fuzzing deep learning libraries. In: Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, pp 1–13
2024
Closest in time.
Guo Q, Cao J, Xie X, Liu S, Li X, Chen B, Peng X (2024) Exploring the potential of chatgpt in automated code refinement: An empirical study. In: Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, pp 1–13
2024
Closest in time.
Liang JT, Yang C, Myers BA (2024) A large-scale survey on the usability of ai programming assistants: Successes and challenges. In: Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, pp 1–13
2024
Closest in time.
OpenAI (2024a) ChatGTP Shared Links FAQ. URL https://help.openai.com/en/articles/7925741-chatgpt-shared-links-faq , accessed: 2024-01-23
2024
Closest in time.
OpenAI (2024b) Create a Shared Link. URL https://help.openai.com/en/articles/7943611-create-a-shared-link , accessed: 2024-01-23
2024
Closest in time.
Wang X, Chen Y, Yuan L, Zhang Y, Li Y, Peng H, Ji H (2024) Executable code actions elicit better llm agents. arXiv preprint arXiv:240201030
2024
Closest in time.
Xiao T, Treude C, Hata H, Matsumoto K (2024) Devgpt: Studying developer-chatgpt conversations. In: Proceedings of the International Conference on Mining Software Repositories (MSR 2024)
2024
Closest in time.