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This paper investigates the application of large language models (LLM) in the domain of mobile application test script generation.
A. Mesbah, A. Van Deursen, and D. Roest, “Invariant-based automatic testing of modern web applications,” IEEE Transactions on Software Engineering , vol. 38, no. 1, pp. 35–53, 2011
2011
Earlier work this paper cites.
F. Wang and W. Du, “A test automation framework based on web,” in 2012 IEEE/ACIS 11th International Conference on Computer and Information Science . IEEE, 2012, pp. 683–687
2012
Earlier work this paper cites.
S. Anand, M. Naik, M. J. Harrold, and H. Yang, “Automated concolic testing of smartphone apps,” in Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering , 2012, pp. 1–11
2012
Earlier work this paper cites.
S. Thummalapenta, P. Devaki, S. Sinha, S. Chandra, S. Gnanasundaram, D. D. Nagaraj, S. Kumar, and S. Kumar, “Efficient and change-resilient test automation: An industrial case study,” in 2013 35th International Conference on Software Engineering (ICSE) . IEEE, 2013, pp. 1002–1011
2013
Earlier work this paper cites.
R. Anbunathan and A. Basu, “An event based test automation framework for android mobiles,” in 2014 International Conference on Contemporary Computing and Informatics (IC3I) . IEEE, 2014, pp. 76–79
2014
Earlier work this paper cites.
V. Dallmeier, B. Pohl, M. Burger, M. Mirold, and A. Zeller, “Webmate: Web application test generation in the real world,” in 2014 IEEE Seventh International Conference on Software Testing, Verification and Validation Workshops . IEEE, 2014, pp. 413–418
2014
Earlier work this paper cites.
D. Amalfitano, A. R. Fasolino, P. Tramontana, B. D. Ta, and A. M. Memon, “Mobiguitar: Automated model-based testing of mobile apps,” IEEE Software , vol. 32, no. 5, pp. 53–59, 2014
2014
Earlier work this paper cites.
D. Xu, W. Xu, M. Kent, L. Thomas, and L. Wang, “An automated test generation technique for software quality assurance,” IEEE transactions on reliability , vol. 64, no. 1, pp. 247–268, 2014
2014
Earlier work this paper cites.
V. Raychev, M. Vechev, and E. Yahav, “Code completion with statistical language models,” in Proceedings of the 35th ACM SIGPLAN conference on programming language design and implementation , 2014, pp. 419–428
2014
Earlier work this paper cites.
Z. Gao, Z. Chen, Y. Zou, and A. M. Memon, “Sitar: Gui test script repair,” Ieee transactions on software engineering , vol. 42, no. 2, pp. 170–186, 2015
2015
Earlier work this paper cites.
H. Tanno and X. Zhang, “Test script generation based on design documents for web application testing,” in 2015 IEEE 39th Annual Computer Software and Applications Conference , vol. 3. IEEE, 2015, pp. 672–673
2015
Earlier work this paper cites.
S. R. Choudhary, A. Gorla, and A. Orso, “Automated test input generation for android: Are we there yet? (e),” in Proceedings of the 2015 30th IEEE/ACM International Conference on Automated Software Engineering . IEEE, 2015, pp. 429–440
2015
Earlier work this paper cites.
B. Yu, L. Ma, and C. Zhang, “Incremental web application testing using page object,” in Proceedings of the 2015 Third IEEE Workshop on Hot Topics in Web Systems and Technologies . IEEE, 2015, pp. 1–6
2015
Earlier work this paper cites.
X. Zeng, D. Li, W. Zheng, F. Xia, Y. Deng, W. Lam, W. Yang, and T. Xie, “Automated test input generation for android: Are we really there yet in an industrial case?” in Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering , 2016, pp. 987–992
2016
Earlier work this paper cites.
K. Mao, M. Harman, and Y. Jia, “Sapienz: Multi-objective automated testing for android applications,” in Proceedings of the 25th International Symposium on Software Testing and Analysis , 2016, pp. 94–105
2016
Earlier work this paper cites.
X. Li, N. Chang, Y. Wang, H. Huang, Y. Pei, L. Wang, and X. Li, “Atom: Automatic maintenance of gui test scripts for evolving mobile applications,” in 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST) . IEEE, 2017, pp. 161–171
2017
Earlier work this paper cites.
Y. Li, Z. Yang, Y. Guo, and X. Chen, “Droidbot: a lightweight ui-guided test input generator for android,” in 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C) . IEEE, 2017, pp. 23–26
2017
Earlier work this paper cites.
T. Su, G. Meng, Y. Chen, K. Wu, W. Yang, Y. Yao, G. Pu, Y. Liu, and Z. Su, “Guided, stochastic model-based gui testing of android apps,” in Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering , 2017, pp. 245–256
2017
Earlier work this paper cites.
T. Gu, C. Cao, T. Liu, C. Sun, J. Deng, X. Ma, and J. Lü, “Aimdroid: Activity-insulated multi-level automated testing for android applications,” in Proceedings of the 2017 IEEE International Conference on Software Maintenance and Evolution . IEEE, 2017, pp. 103–114
2017
Earlier work this paper cites.
G. de Cleva Farto and A. T. Endo, “Reuse of model-based tests in mobile apps,” in Proceedings of the XXXI Brazilian Symposium on Software Engineering , 2017, pp. 184–193
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
F. Behrang and A. Orso, “Test migration for efficient large-scale assessment of mobile app coding assignments,” in Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis , 2018, pp. 164–175
2018
Earlier work this paper cites.
M. Iyama, H. Kirinuki, H. Tanno, and T. Kurabayashi, “Automatically generating test scripts for gui testing,” in 2018 IEEE International Conference on Software Testing, Verification and Validation Workshops . IEEE, 2018, pp. 146–150
2018
Cited alongside, same era.
A. Rau, J. Hotzkow, and A. Zeller, “Poster: Efficient gui test generation by learning from tests of other apps,” in 2018 IEEE/ACM 40th International Conference on Software Engineering: Companion . IEEE, 2018, pp. 370–371
2018
Cited alongside, same era.
——, “Transferring tests across web applications,” in Web Engineering: 18th International Conference, ICWE 2018, Cáceres, Spain, June 5-8, 2018, Proceedings 18 . Springer, 2018, pp. 50–64
2018
Cited alongside, same era.
Y. Koroglu, A. Sen, O. Muslu, Y. Mete, C. Ulker, T. Tanriverdi, and Y. Donmez, “Qbe: Qlearning-based exploration of android applications,” in 2018 IEEE 11th International Conference on Software Testing, Verification and Validation (ICST) . IEEE, 2018, pp. 105–115
2018
Google, “https://developer.android.com/studio/test/other-testing-tools/monkey,” 2022
2022
Later among the works it cites.
Z. Lv, C. Peng, Z. Zhang, T. Su, K. Liu, and P. Yang, “Fastbot2: Reusable automated model-based gui testing for android enhanced by reinforcement learning,” in 37th IEEE/ACM International Conference on Automated Software Engineering , 2022, pp. 1–5
2022
Later among the works it cites.
2022
Later among the works it cites.
J. Wei, X. Wang, D. Schuurmans, M. Bosma, F. Xia, E. Chi, Q. V. Le, D. Zhou et al. , “Chain-of-thought prompting elicits reasoning in large language models,” Advances in Neural Information Processing Systems , vol. 35, pp. 24 824–24 837, 2022
2022
Later among the works it cites.
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Cited alongside, same era.
X. Qin, H. Zhong, and X. Wang, “Testmig: Migrating gui test cases from ios to android,” in Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis , 2019, pp. 284–295
2019
Cited alongside, same era.
——, “Test migration between mobile apps with similar functionality,” in 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 2019, pp. 54–65
2019
Cited alongside, same era.
J.-W. Lin, R. Jabbarvand, and S. Malek, “Test transfer across mobile apps through semantic mapping,” in 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 2019, pp. 42–53
2019
Cited alongside, same era.
M. Biagiola, A. Stocco, F. Ricca, and P. Tonella, “Diversity-based web test generation,” in Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering , 2019, pp. 142–153
2019
Cited alongside, same era.
T. D. White, G. Fraser, and G. J. Brown, “Improving random gui testing with image-based widget detection,” in Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis , 2019, pp. 307–317
2019
Cited alongside, same era.
Y. Li, Z. Yang, Y. Guo, and X. Chen, “Humanoid: A deep learning-based approach to automated black-box android app testing,” in 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 2019, pp. 1070–1073
2019
Cited alongside, same era.
J. Wang, Y. Jiang, C. Xu, C. Cao, X. Ma, and J. Lu, “Combodroid: generating high-quality test inputs for android apps via use case combinations,” in Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering , 2020, pp. 469–480
2020
Cited alongside, same era.
M. Pan, A. Huang, G. Wang, T. Zhang, and X. Li, “Reinforcement learning based curiosity-driven testing of android applications,” in Proceedings of the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis , 2020, pp. 153–164
2020
Cited alongside, same era.
P. Vaithilingam, T. Zhang, and E. L. Glassman, “Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models,” in Chi conference on human factors in computing systems extended abstracts , 2022, pp. 1–7
2022
Later among the works it cites.
T. Ahmed and P. Devanbu, “Few-shot training llms for project-specific code-summarization,” in Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering , 2022, pp. 1–5
2022
Later among the works it cites.
2022
Later among the works it cites.
2022
Later among the works it cites.
I. Ozkaya, “Application of large language models to software engineering tasks: Opportunities, risks, and implications,” IEEE Software , vol. 40, no. 3, pp. 4–8, 2023
2023
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L. Gao, A. Madaan, S. Zhou, U. Alon, P. Liu, Y. Yang, J. Callan, and G. Neubig, “Pal: Program-aided language models,” in International Conference on Machine Learning . PMLR, 2023, pp. 10 764–10 799
2023
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2023
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S. I. Ross, F. Martinez, S. Houde, M. Muller, and J. D. Weisz, “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 , 2023, pp. 491–514
2023
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K. T. Le, G. Rashidi, and A. Andrzejak, “A methodology for refined evaluation of neural code completion approaches,” Data Mining and Knowledge Discovery , vol. 37, no. 1, pp. 167–204, 2023
2023
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S. MacNeil, A. Tran, A. Hellas, J. Kim, S. Sarsa, P. Denny, S. Bernstein, and J. Leinonen, “Experiences from using code explanations generated by large language models in a web software development e-book,” in Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 , 2023, pp. 931–937
2023
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Y. Su, C. Wan, U. Sethi, S. Lu, M. Musuvathi, and S. Nath, “Hotgpt: How to make software documentation more useful with a large language model?” in Proceedings of the 19th Workshop on Hot Topics in Operating Systems , 2023, pp. 87–93
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