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Test oracles play a crucial role in software testing, enabling effective bug detection.
J. Andrews, L. Briand, and Y. Labiche, “Is mutation an appropriate tool for testing experiments? [software testing],” in Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005. , 2005, pp. 402–411
2005
Earlier work this paper cites.
C. Pacheco and M. D. Ernst, “Randoop: feedback-directed random testing for java,” in Companion to the 22nd ACM SIGPLAN conference on Object-oriented programming systems and applications companion , 2007, pp. 815–816
2007
Earlier work this paper cites.
G. J. Myers, C. Sandler, and T. Badgett, The art of software testing . John Wiley & Sons, 2011
2011
Earlier work this paper cites.
G. Fraser and A. Arcuri, “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 , 2011, pp. 416–419. [Online]. Available: https://doi.org/10.1145/2025113.2025179
2011
Earlier work this paper cites.
A. M. Porrello, “Death and denial: The failure of the therac-25, a medical linear accelerator,” Death and Denial: The Failure of the THERAC-25, AMedical Linear Accelerator , 2012
2012
Earlier work this paper cites.
R. Pandita, X. Xiao, H. Zhong, T. Xie, S. Oney, and A. Paradkar, “Inferring method specifications from natural language api descriptions,” in 2012 34th International Conference on Software Engineering (ICSE) , 2012, pp. 815–825
2012
Earlier work this paper cites.
S. H. Tan, D. Marinov, L. Tan, and G. T. Leavens, “@tcomment: Testing javadoc comments to detect comment-code inconsistencies,” in 2012 IEEE Fifth International Conference on Software Testing, Verification and Validation , 2012, pp. 260–269
2012
Earlier work this paper cites.
D. Schuler and A. Zeller, “Checked coverage: an indicator for oracle quality,” Software testing, verification and reliability , vol. 23, no. 7, pp. 531–551, 2013
2013
Earlier work this paper cites.
Synopsys Editorial Team, “Coverity report on the ‘goto fail’ bug,” blog post, Synopsys, Mountain View, CA, Feb. 25, 2014; http://security.coverity.com/blog/2014/Feb/a-quick-post-on-apple-security-55471-aka-goto-fail.html
2014
Earlier work this paper cites.
——, “A large-scale evaluation of automated unit test generation using evosuite,” ACM Trans. Softw. Eng. Methodol. , vol. 24, no. 2, dec 2014. [Online]. Available: https://doi.org/10.1145/2685612
2014
Earlier work this paper cites.
R. Just, D. Jalali, and M. D. Ernst, “Defects4j: A database of existing faults to enable controlled testing studies for java programs,” in Proceedings of the 2014 International Symposium on Software Testing and Analysis , 2014, pp. 437–440. [Online]. Available: https://doi.org/10.1145/2610384.2628055
2014
Earlier work this paper cites.
R. Just, D. Jalali, L. Inozemtseva, M. D. Ernst, R. Holmes, and G. Fraser, “Are mutants a valid substitute for real faults in software testing?” in Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering , ser. FSE 2014. New York, NY, USA: Association for Computing Machinery, 2014, p. 654–665. [Online]. Available: https://doi.org/10.1145/2635868.2635929
2014
Earlier work this paper cites.
Y. Zhang and A. Mesbah, “Assertions are strongly correlated with test suite effectiveness,” in Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering , 2015, pp. 214–224. [Online]. Available: https://doi.org/10.1145/2786805.2786858
2015
Earlier work this paper cites.
S. Rani, B. Suri, and S. K. Khatri, “Experimental comparison of automated mutation testing tools for java,” in 2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions) , 2015, pp. 1–6
2015
Earlier work this paper cites.
H. News, “Twitter outage report,” 2016, https://news.ycombinator.com/item?id=8810157
2016
Earlier work this paper cites.
A. Goffi, A. Gorla, M. D. Ernst, and M. Pezzè, “Automatic generation of oracles for exceptional behaviors,” in Proceedings of the 25th International Symposium on Software Testing and Analysis , ser. ISSTA 2016. New York, NY, USA: Association for Computing Machinery, 2016, p. 213–224. [Online]. Available: https://doi.org/10.1145/2931037.2931061
2016
Earlier work this paper cites.
H. Coles, T. Laurent, C. Henard, M. Papadakis, and A. Ventresque, “Pit: a practical mutation testing tool for java,” in Proceedings of the 25th international symposium on software testing and analysis , 2016, pp. 449–452. [Online]. Available: https://doi.org/10.1145/2931037.2948707
2016
Earlier work this paper cites.
D. Lin, J. Koppel, A. Chen, and A. Solar-Lezama, “Quixbugs: a multi-lingual program repair benchmark set based on the quixey challenge,” in Proceedings Companion of the 2017 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity , ser. SPLASH Companion 2017. New York, NY, USA: Association for Computing Machinery, 2017, p. 55–56. [Online]. Available: https://doi.org/10.1145/3135932.3135941
2017
Earlier work this paper cites.
T. Laurent, M. Papadakis, M. Kintis, C. Henard, Y. L. Traon, and A. Ventresque, “Assessing and improving the mutation testing practice of pit,” in 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST) , 2017, pp. 430–435
2017
Cited alongside, same era.
A. Blasi, A. Goffi, K. Kuznetsov, A. Gorla, M. D. Ernst, M. Pezzè, and S. D. Castellanos, “Translating code comments to procedure specifications,” in Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis , ser. ISSTA 2018. New York, NY, USA: Association for Computing Machinery, 2018, p. 242–253. [Online]. Available: https://doi.org/10.1145/3213846.3213872
2018
Cited alongside, same era.
M. Kintis, M. Papadakis, A. Papadopoulos, E. Valvis, N. Malevris, and Y. Le Traon, “How effective are mutation testing tools? an empirical analysis of java mutation testing tools with manual analysis and real faults,” Empirical Software Engineering , vol. 23, no. 4, pp. 2426–2463, 2018
2018
Cited alongside, same era.
S. B. Hossain, M. B. Dwyer, S. Elbaum, and A. Nguyen-Tuong, “Measuring and mitigating gaps in structural testing,” in 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) . IEEE, 2023, pp. 1712–1723
2023
Later among the works it cites.
S. B. Hossain, A. Filieri, M. B. Dwyer, S. Elbaum, and W. Visser, “Neural-based test oracle generation: A large-scale evaluation and lessons learned,” in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering , ser. ESEC/FSE 2023. NY, USA: Association for Computing Machinery, 2023, p. 120–132. [Online]. Available: https://doi.org/10.1145/3611643.3616265
2023
Later among the works it cites.
Z. Li, C. Wang, Z. Liu, H. Wang, D. Chen, S. Wang, and C. Gao, “Cctest: Testing and repairing code completion systems,” in 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) . IEEE, 2023, pp. 1238–1250
2023
Later among the works it cites.
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C. Watson, M. Tufano, K. Moran, G. Bavota, and D. Poshyvanyk, “On learning meaningful assert statements for unit test cases,” in Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering , 2020, pp. 1398–1409. [Online]. Available: https://doi.org/10.1145/3377811.3380429
2020
Cited alongside, same era.
2020
Cited alongside, same era.
2020
Cited alongside, same era.
J. Rasley, S. Rajbhandari, O. Ruwase, and Y. He, “Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters,” in Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining , 2020, pp. 3505–3506
2020
Cited alongside, same era.
A. Blasi, A. Gorla, M. D. Ernst, M. Pezzè, and A. Carzaniga, “Memo: Automatically identifying metamorphic relations in javadoc comments for test automation,” Journal of Systems and Software , vol. 181, p. 111041, 2021. [Online]. Available: https://doi.org/10.1016/j.jss.2021.111041
2021
Cited alongside, same era.
E. M. Bender, T. Gebru, A. McMillan-Major, and S. Shmitchell, “On the dangers of stochastic parrots: Can language models be too big?” in Proceedings of the 2021 ACM conference on fairness, accountability, and transparency , 2021, pp. 610–623
2021
Cited alongside, same era.
2021
Cited alongside, same era.
G. Petrovic, M. Ivankovic, G. Fraser, and R. Just, “Practical mutation testing at scale: A view from google,” IEEE Transactions on Software Engineering , 2021
2021
Cited alongside, same era.
G. Petrović, M. Ivanković, G. Fraser, and R. Just, “Does mutation testing improve testing practices?” in 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) . IEEE, 2021, pp. 910–921. [Online]. Available: https://doi.org/10.1109/ICSE43902.2021.00087
2021
Cited alongside, same era.
M. Jin, S. Shahriar, M. Tufano, X. Shi, S. Lu, N. Sundaresan, and A. Svyatkovskiy, “Inferfix: End-to-end program repair with llms,” in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering , 2023, pp. 1646–1656
2023
Later among the works it cites.
C. Lemieux, J. P. Inala, S. K. Lahiri, and S. Sen, “Codamosa: Escaping coverage plateaus in test generation with pre-trained large language models,” in 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) . IEEE, 2023, pp. 919–931
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
E. Nijkamp, B. Pang, H. Hayashi, L. Tu, H. Wang, Y. Zhou, S. Savarese, and C. Xiong, “Codegen: An open large language model for code with multi-turn program synthesis,” 2023
2023
Later among the works it cites.
Z. Liu, K. Liu, X. Xia, and X. Yang, “Towards more realistic evaluation for neural test oracle generation,” in Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis , 2023, pp. 589–600
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
D. Nam, A. Macvean, V. Hellendoorn, B. Vasilescu, and B. Myers, “Using an llm to help with code understanding,” in 2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE) . IEEE Computer Society, 2024, pp. 881–881
2024
Closest in time.
M. Schäfer, S. Nadi, A. Eghbali, and F. Tip, “An empirical evaluation of using large language models for automated unit test generation,” IEEE Transactions on Software Engineering , vol. 50, no. 1, pp. 85–105, 2024
2024
Closest in time.
S. B. Hossain, N. Jiang, Q. Zhou, X. Li, W.-H. Chiang, Y. Lyu, H. Nguyen, and O. Tripp, “A deep dive into large language models for automated bug localization and repair,” Proc. ACM Softw. Eng. , vol. 1, no. FSE, Jul. 2024. [Online]. Available: https://doi.org/10.1145/3660773
2024
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Hugging Face, “Hugging face: The ai community building the future,” https://huggingface.co/ , 2024, accessed: 2024-05-1
2024
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X. Hou, Y. Zhao, Y. Liu, Z. Yang, K. Wang, L. Li, X. Luo, D. Lo, J. Grundy, and H. Wang, “Large language models for software engineering: A systematic literature review,” 2024
2024
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S. B. Hossain, “Ensuring critical properties of test oracles for effective bug detection,” in Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings , ser. ICSE-Companion’24. New York, NY, USA: Association for Computing Machinery, 2024, p. 176–180. [Online]. Available: https://doi.org/10.1145/3639478.3639791
2024
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