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Test-driven development (TDD) is a widely-employed software development practice that mandates writing test cases based on requirements before writing the actual code.
Language models are few-shot learners
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al., 2020 · 1901
Earlier work this paper cites.
Way off-policy batch deep reinforcement learning of implicit human preferences in dialog
Jaques, N., Ghandeharioun, A., Shen, J.H., Ferguson, C., Lapedriza, A., Jones, N., Gu, S., Picard, R., 2019 · 1907
Earlier work this paper cites.
Codesearchnet challenge: Evaluating the state of semantic code search
Husain, H., Wu, H.H., Gazit, T., Allamanis, M., Brockschmidt, M., 2019 · 1909
Earlier work this paper cites.
Fine-tuning language models from human preferences
Ziegler, D.M., Stiennon, N., Wu, J., Brown, T.B., Radford, A., Amodei, D., Christiano, P., Irving, G., 2019 · 1909
Earlier work this paper cites.
On information and sufficiency
Kullback, S., Leibler, R.A., 1951 · 1951
Earlier work this paper cites.
Actor-critic algorithms
Konda, V., Tsitsiklis, J., 1999 · 1999
Earlier work this paper cites.
Manifesto for agile software development
Beck, K., Beedle, M., Van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning, J., Highsmith, J., Hunt, A., Jeffries, R., et al., 2001 · 2001
Earlier work this paper cites.
Experiment about test-first programming
Mueller, M.M., Hagner, O., 2002 · 2002
Earlier work this paper cites.
Test driven development: A practical guide
Astels, D., 2003 · 2003
Earlier work this paper cites.
The object primer: Agile model-driven development with UML 2.0
Ambler, S.W., 2004 · 2004
Earlier work this paper cites.
The effect of code coverage on fault detection under different testing profiles, in: Proceedings of the 1st International Workshop on Advances in Model-based Testing, pp. 1–7
Cai, X., Lyu, M.R., 2005 · 2005
Earlier work this paper cites.
On the effectiveness of the test-first approach to programming
Erdogmus, H., Morisio, M., Torchiano, M., 2005 · 2005
Earlier work this paper cites.
Randoop: feedback-directed random testing for java, in: Companion to the 22nd ACM SIGPLAN conference on Object-oriented programming systems and applications companion, pp. 815–816
Pacheco, C., Ernst, M.D., 2007 · 2007
Earlier work this paper cites.
Feedback-directed random test generation, in: ICSE 2007, Proceedings of the 29th International Conference on Software Engineering, Minneapolis, MN, USA. pp. 75–84
Pacheco, C., Lahiri, S.K., Ernst, M.D., Ball, T., 2007 · 2007
Earlier work this paper cites.
Does test-driven development really improve software design quality?
Janzen, D., Saiedian, H., 2008 · 2008
Earlier work this paper cites.
Unit test case generation with transformers and focal context
Tufano, M., Drain, D., Svyatkovskiy, A., Deng, S.K., Sundaresan, N., 2020 · 2009
Earlier work this paper cites.
An analysis and survey of the development of mutation testing
Jia, Y., Harman, M., 2010 · 2010
Earlier work this paper cites.
The impact of test-first programming on branch coverage and mutation score indicator of unit tests: An experiment
Madeyski, L., 2010 · 2010
Earlier work this paper cites.
Evosuite: automatic test suite generation for object-oriented software, in: Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering, pp. 416–419
Fraser, G., Arcuri, A., 2011 · 2011
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D.P., Ba, J., 2014 · 2014
Earlier work this paper cites.
How effective are code coverage criteria?, in: 2015 IEEE International Conference on Software Quality, Reliability and Security, IEEE. pp. 151–156
Hemmati, H., 2015 · 2015
Earlier work this paper cites.
High-dimensional continuous control using generalized advantage estimation
Schulman, J., Moritz, P., Levine, S., Jordan, M., Abbeel, P., 2015 · 2015
Cited alongside, same era.
An actor-critic algorithm for sequence prediction
Bahdanau, D., Brakel, P., Xu, K., Goyal, A., Lowe, R., Pineau, J., Courville, A., Bengio, Y., 2016 · 2016
Cited alongside, same era.
On the diffusion of test smells in automatically generated test code: An empirical study, in: Proceedings of the 9th international workshop on search-based software testing, pp. 5–14
Palomba, F., Di Nucci, D., Panichella, A., Oliveto, R., De Lucia, A., 2016 · 2016
Cited alongside, same era.
An industrial evaluation of unit test generation: Finding real faults in a financial application, in: 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP), IEEE. pp. 263–272
Almasi, M.M., Hemmati, H., Fraser, G., Arcuri, A., Benefelds, J., 2017 · 2017
Cited alongside, same era.
Test driven development: By example
Beck, K., 2022 · 2022
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Codet: Code generation with generated tests
Chen, B., Zhang, F., Nguyen, A., Zan, D., Lin, Z., Lou, J.G., Chen, W., 2022 · 2022
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Toga: A neural method for test oracle generation, in: Proceedings of the 44th International Conference on Software Engineering, pp. 2130–2141
Dinella, E., Ryan, G., Mytkowicz, T., Lahiri, S.K., 2022 · 2022
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Incoder: A generative model for code infilling and synthesis
Fried, D., Aghajanyan, A., Lin, J., Wang, S., Wallace, E., Shi, F., Zhong, R., Yih, W.t., Zettlemoyer, L., Lewis, M., 2022 · 2022
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Hyperparameter tuning for deep reinforcement learning applications
Kiran, M., Ozyildirim, M., 2022 · 2022
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Deep reinforcement learning from human preferences
Christiano, P.F., Leike, J., Brown, T., Martic, M., Legg, S., Amodei, D., 2017 · 2017
Cited alongside, same era.
Proximal policy optimization algorithms
Schulman, J., Wolski, F., Dhariwal, P., Radford, A., Klimov, O., 2017 · 2017
Cited alongside, same era.
Translating code comments to procedure specifications, in: Proceedings of the 27th ACM SIGSOFT international symposium on software testing and analysis, pp. 242–253
Blasi, A., Goffi, A., Kuznetsov, K., Gorla, A., Ernst, M.D., Pezzè, M., Castellanos, S.D., 2018 · 2018
Cited alongside, same era.
Reinforcement learning: An introduction
Sutton, R.S., Barto, A.G., 2018 · 2018
Cited alongside, same era.
Scented since the beginning: On the diffuseness of test smells in automatically generated test code
Grano, G., Palomba, F., Di Nucci, D., De Lucia, A., Gall, H.C., 2019 · 2019
Cited alongside, same era.
Mutation testing advances: an analysis and survey, in: Advances in Computers. Elsevier. volume 112, pp. 275–378
Papadakis, M., Kintis, M., Zhang, J., Jia, Y., Le Traon, Y., Harman, M., 2019 · 2019
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., Liu, P.J., 2020 · 2020
Cited alongside, same era.
Learning to summarize with human feedback
Stiennon, N., Ouyang, L., Wu, J., Ziegler, D., Lowe, R., Voss, C., Radford, A., Amodei, D., Christiano, P.F., 2020 · 2020
Cited alongside, same era.
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Coderl: Mastering code generation through pretrained models and deep reinforcement learning
Le, H., Wang, Y., Gotmare, A.D., Savarese, S., Hoi, S.C.H., 2022 · 2022
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Pynguin: Automated unit test generation for python, in: Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings, pp. 168–172
Lukasczyk, S., Fraser, G., 2022 · 2022
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Training language models to follow instructions with human feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al., 2022 · 2022
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Compilable neural code generation with compiler feedback
Wang, X., Wang, Y., Wan, Y., Mi, F., Li, Y., Zhou, P., Liu, J., Wu, H., Jiang, X., Liu, Q., 2022 · 2022
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A3test: Assertion-augmented automated test case generation
Alagarsamy, S., Tantithamthavorn, C., Aleti, A., 2023 · 2023
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Automatic creation of acceptance tests by extracting conditionals from requirements: Nlp approach and case study
Fischbach, J., Frattini, J., Vogelsang, A., Mendez, D., Unterkalmsteiner, M., Wehrle, A., Henao, P.R., Yousefi, P., Juricic, T., Radduenz, J., et al., 2023 · 2023
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Exploring the potential of chatgpt in automated code refinement: An empirical study
Guo, Q., Cao, J., Xie, X., Liu, S., Li, X., Chen, B., Peng, X., 2023 · 2023
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Large language models for software engineering: A systematic literature review
Hou, X., Zhao, Y., Liu, Y., Yang, Z., Wang, K., Li, L., Luo, X., Lo, D., Grundy, J., Wang, H., 2023 · 2023
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Starcoder: may the source be with you!
Li, R., Allal, L.B., Zi, Y., Muennighoff, N., Kocetkov, D., Mou, C., Marone, M., Akiki, C., Li, J., Chim, J., et al., 2023 · 2023
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OpenAI, 2023 · 2023
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Code llama: Open foundation models for code
Rozière, B., Gehring, J., Gloeckle, F., Sootla, S., Gat, I., Tan, X.E., Adi, Y., Liu, J., Remez, T., Rapin, J., et al., 2023 · 2023
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Exploring the effectiveness of large language models in generating unit tests
Siddiq, M.L., Santos, J., Tanvir, R.H., Ulfat, N., Rifat, F.A., Lopes, V.C., 2023 · 2023
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Chatgpt vs sbst: A comparative assessment of unit test suite generation
Tang, Y., Liu, Z., Zhou, Z., Luo, X., 2023 · 2023
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Chatunitest: a chatgpt-based automated unit test generation tool
Xie, Z., Chen, Y., Zhi, C., Deng, S., Yin, J., 2023 · 2023
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No more manual tests? evaluating and improving chatgpt for unit test generation
Yuan, Z., Lou, Y., Liu, M., Ding, S., Wang, K., Chen, Y., Peng, X., 2023 · 2023
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