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With the recent advancement of Artificial Intelligence (AI) and Large Language Models (LLMs), AI-based code generation tools become a practical solution for software development.
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Understanding quantum software engineering challenges an empirical study on stack exchange forums and github issues, in: Proceedings of 37th IEEE International Conference on Software Maintenance and Evolution (ICSME)
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Is github copilot a substitute for human pair-programming? an empirical study, in: Proceedings of the 44th International Conference on Software Engineering (ICSE): Companion, IEEE. pp. 319–321
Imai, S., 2022 · 2022
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Choose your programming copilot: A comparison of the program synthesis performance of github copilot and genetic programming, in: Proceedings of the 24th Genetic and Evolutionary Computation Conference (GECCO), ACM. pp. 1019–1027
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Assessing the quality of github copilot’s code generation, in: Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE), ACM. pp. 62–71
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Github copilot ai pair programmer: Asset or liability?
Moradi Dakhel, A., Majdinasab, V., Nikanjam, A., Khomh, F., Desmarais, M.C., Jiang, Z.M., 2023 · 2023
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Zhao, S., 2023 · 2023
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How readable is model-generated code? examining readability and visual inspection of github copilot, in: Proceedings of the 37th International Conference on Automated Software Engineering (ASE), ACM. pp. 1–5
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Will affective computing emerge from foundation models and general artificial intelligence? a first evaluation of chatgpt
Amin, M.M., Cambria, E., Schuller, B.W., 2023 · 2023
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Asare, O., Nagappan, M., Asokan, N., 2023 · 2023
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Barke, S., James, M.B., Polikarpova, N., 2023 · 2023
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Bird, C., Ford, D., Zimmermann, T., Forsgren, N., Kalliamvakou, E., Lowdermilk, T., Gazit, I., 2023 · 2023
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Chen, X., Ye, J., Zu, C., Xu, N., Zheng, R., Peng, M., Zhou, J., Gui, T., Zhang, Q., Huang, X., 2023 · 2023
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de Dieu, M.J., Liang, P., Shahin, M., Khan, A.A., 2023 · 2023
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Lost at c: A user study on the security implications of large language model code assistants, in: Proceedings of the 32nd USENIX Security Symposium (USENIX Security), USENIX. pp. 2205–2222
Gustavo, S., Hammond, P., Teo, N., Ramesh, K., Brendan, D.G., Siddharth, G., 2023 · 2023
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Fu, Y., Liang, P., Tahir, A., Li, Z., Shahin, M., Yu, J., 2024 · 2024
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Gartner Identifies the Top 10 Strategic Technology Trends for 2024
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A survey on large language models for code generation
Jiang, J., Wang, F., Shen, J., Kim, S., Kim, S., 2024 · 2024
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A large-scale survey on the usability of ai programming assistants: Successes and challenges, in: Proceedings of the 45th International Conference on Software Engineering (ICSE), ACM. pp. 1–13
Liang, J.T., Yang, C., Myers, B.A., 2024 · 2024
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Copilot.vim
Pope, T., 2024 · 2024
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Tabnine - The AI code assistant that you control
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GitHub Copilot drives revenue growth amid subscriber base expansion
Wilkinson, L., 2024 · 2024
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Copilot refinement: Addressing code smells in copilot-generated python code
Zhang, B., Liang, P., Feng, Q., Fu, Y., Li, Z., 2024 · 2024
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Dataset of the Paper “Exploring the Problems, their Causes, and Solutions of AI Pair Programming: A Study with Practitioners of GitHub Copilot”
Zhou, X., Liang, P., Zhang, B., Li, Z., Ahmad, A., Shahin, M., Waseem, M., 2024 · 2024
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Measuring github copilot’s impact on productivity
Ziegler, A., Kalliamvakou, E., Li, X.A., Rice, A., Rifkin, D., Simister, S., Sittampalam, G., Aftandilian, E., 2024 · 2024
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