Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey | Paper Citation Record

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This paper cites In: 2023 IEEE International Conference On Artificial Intelligence Testing (AITest).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2023 IEEE International Conference On Artificial Intelligence Testing (AITest)

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This paper cites Ontologies for software engineering and software technology pp.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Ontologies for software engineering and software technology pp

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Seke

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This paper cites In: Knowledge Engineering and Knowledge Management: 20th International Conference, EKAW 2016, Bologna, Italy, November 19-23, 2016, Proceedings 20.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Knowledge Engineering and Knowledge Management: 20th International Conference, EKAW 2016, Bologna, Italy, November 19-23, 2016, Proceedings 20

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2023 Innovations in Intelligent Systems and Applications Conference (ASYU)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Springer Science & Business Media (2006)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Companion Proceedings of the 30th Interna- tional Conference on Intelligent User Interfaces

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2022 IEEE Aerospace Conference (AERO)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Proceedings of the 3rd ACM/IEEE International Conference on Automation of Software Test

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Early Research Achievements (ERA)

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This paper cites Software Quality Journal25, 1269–1305 (2017).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Software Quality Journal25, 1269–1305 (2017)

Reference 14

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey International Journal on Software Tools for Technology Transfer16, 559–568 (2014)

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This paper cites Software testing, verification and reliability26(2), 119–148 (2016) 12 I.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Software testing, verification and reliability26(2), 119–148 (2016) 12 I

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This paper cites https://doi.org/10.48550/arXiv.2504.07244, http:// arxiv.org/abs/2504.07244, arXiv:2504.07244 [cs].

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey https://doi.org/10.48550/arXiv.2504.07244, http:// arxiv.org/abs/2504.07244, arXiv:2504.07244 [cs]

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2025 IEEE Conference on Software Testing, Verification and Validation (ICST)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2023 5th Novel Intelligent and Leading Emerging Sciences Conference (NILES)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2022 IEEE International Conference On Artificial Intelligence Testing (AITest)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2023 International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2024 5th IEEE Global Conference for Advancement in Technology (GCAT)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Proceedings of the 1st ACM SIGSOFT International Workshop on Languages and Tools for Next-Generation Testing

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Conceptual Modeling: 37th International Conference, ER 2018, Xi’an, China, October 22–25, 2018, Proceedings 37

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2025 IEEE Interna- tional Conference on Software Testing, Verification and Validation Workshops (ICSTW)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2024 IEEE Frontiers in Education Conference (FIE)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2024 International Telecommunications Conference The ai4st taxonomy and its use 13 (ITC-Egypt)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey TOGLL: Correct and Strong Test Oracle Generation with LLMs

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey istqb.org

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2025 Fifth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2020 10th International Con- ference on Cloud Computing, Data Science & Engineering (Confluence)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Proceedings of the 5th ACM/IEEE International Conference on Automation of Software Test (AST 2024)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Proceedings of the XXIII Brazilian Symposium on Software Quality

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey W3C recommen- dation 10(10), 2004 (2004)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2024 International Conference on Circuit, Systems and Communication (ICCSC)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2024 36th International Conference on Software Engineering Education and Train- ing (CSEE&T)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey https://doi.org/10.1109/AST66626.2025.00008, http://arxiv.org/abs/2502

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2023 IEEE 15th International Con- ference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Envi- ronment, and Management (HNICEM)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2011 IEEE Third International Conference on Cloud Computing Technology and Science

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Communications of the ACM55(11), 12–12 (2012)

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Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Data Intelligence 2(3), 379–416 (2020)

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This paper cites Augmenting software engineering with AI - The ai4se taxonomy and its use.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Augmenting software engineering with AI - The ai4se taxonomy and its use

Reference 49

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T19:53:53.106156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c094f4c2-99a3-4987-8bca-d6d7d46e2137 · outbound

This paper cites an unresolved cited work.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:53:55.455367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f4eef82b-d56b-4fce-b914-ffc53cc1ef90 · outbound

This paper cites an unresolved cited work.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:53:55.441602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 00cf1d85-2ef1-4203-ae9c-6500fa1d2d42 · outbound

This paper cites com/schieferdecker/ai4stpaper.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey com/schieferdecker/ai4stpaper

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.427898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f22f85e8-964a-4be3-9bc2-5f8b46412d58 · outbound

This paper cites an unresolved cited work.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:53:55.414447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ca5afed6-445b-44e8-bc24-f8f3716518b1 · outbound

This paper cites In: Proceedings of the 12th International Workshop on Automating TEST Case Design, Selection, and Evaluation.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Proceedings of the 12th International Workshop on Automating TEST Case Design, Selection, and Evaluation

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T19:53:52.293736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b236a8a-a199-4452-b340-fd5c14b8cdfd · outbound

This paper cites In: 29th Annual International Computer Software and Application Conference (COMPSAC), Edinburgh, UK.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 29th Annual International Computer Software and Application Conference (COMPSAC), Edinburgh, UK

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.399801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4499e3b5-4a61-4343-9632-6719a672832b · outbound

This paper cites Ap- plied Ontology 12(1), 59–90 (2017).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Ap- plied Ontology 12(1), 59–90 (2017)

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.380074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c485ef4b-8de3-45ed-af5c-5b0bf6a728de · outbound

This paper cites strengthening the bond between development and test.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey strengthening the bond between development and test

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.355864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a7c3dfe6-c8b2-4703-94db-38f460d21d08 · outbound

This paper cites an unresolved cited work.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:53:55.313246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fef3de41-9536-4f62-a9c7-a40a3b1e3c66 · outbound

This paper cites In: Central European conference on information and intelligent systems.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Central European conference on information and intelligent systems

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.298668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 72e9f71d-af7f-4570-9cab-e1c13649ad84 · outbound

This paper cites In: 2021 IEEE International Conference on Artificial Intelligence Testing (AITest).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2021 IEEE International Conference on Artificial Intelligence Testing (AITest)

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T19:53:52.321435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 802eb737-ffd9-465b-9221-987cacd3d253 · outbound

This paper cites In: CIbSE.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: CIbSE

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.283697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c632f740-8afb-4908-a519-054ee1e30e45 · outbound

This paper cites Information and Software Technology123, 106298 (2020) The ai4st taxonomy and its use 15.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Information and Software Technology123, 106298 (2020) The ai4st taxonomy and its use 15

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.268087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3dd7c4c0-5009-49e3-9b8b-e40aeb4e1f78 · outbound

This paper cites Information and Software Technology 85, 43–59 (May 2017).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Information and Software Technology 85, 43–59 (May 2017)

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T19:53:52.334206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 576cdb20-c6a3-45a4-b8e7-8e8202beeb87 · outbound

This paper cites Software testing, verification and reliability22(5), 297–312 (2012).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Software testing, verification and reliability22(5), 297–312 (2012)

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.252517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7c85f1d4-0e80-4830-bd3e-04cea2878538 · outbound

This paper cites In: 2015 10th Iberian Conference on Information Systems and Technologies (CISTI).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2015 10th Iberian Conference on Information Systems and Technologies (CISTI)

Reference 65

Resolution: metadata mismatch; raw_fallback, observed 2026-08-15T19:53:52.942393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32da5404-b536-424a-af30-0dcc0b4e3825 · outbound

This paper cites In: Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T19:53:52.346952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86fb0cac-5cd4-4707-a9ad-6bf8362aff2a · outbound

This paper cites an unresolved cited work.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:53:55.236232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 05bc1029-6596-4b37-a047-e47b445e7f7d · outbound

This paper cites an unresolved cited work.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:53:55.220620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e3e03ecf-ce6b-4ac2-8695-8d4d930d2d4c · outbound

This paper cites In: 2024 IEEE 15th International Conference on Software Engineering and Service Science (ICSESS).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2024 IEEE 15th International Conference on Software Engineering and Service Science (ICSESS)

Reference 69

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T19:53:52.798638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e65caaca-fc86-4024-a8f7-5f186af2529a · outbound

This paper cites In: 2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE)

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.203465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f7fbc2f9-88ea-4205-b7b7-ddaf6ff5886f · outbound

This paper cites In: Software Evolution with UML and XML, pp.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: Software Evolution with UML and XML, pp

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:53:55.188226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 08af4648-0718-40f0-ba60-6da87f877e93 · outbound

This paper cites In: 2023 38th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW).

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey In: 2023 38th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T19:53:52.376098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c4f3d4b-5bcf-46ca-b95c-29be1c23c42a · outbound

This paper cites https://doi.org/10.1109/ICSTW64639.2025.10962517, https: //ieeexplore.ieee.org/document/10962517/.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey https://doi.org/10.1109/ICSTW64639.2025.10962517, https: //ieeexplore.ieee.org/document/10962517/

Reference 199

Resolution: unresolved; no resolver link, observed 2026-08-15T19:53:52.168849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c41ba8d4-6a60-4fb9-be1a-0794bbcf5045 · outbound

This paper cites https://doi.org/10.1109/ICAICE63571.2024.10863866, https: //ieeexplore.ieee.org/document/10863866/.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey https://doi.org/10.1109/ICAICE63571.2024.10863866, https: //ieeexplore.ieee.org/document/10863866/

Reference 810

Resolution: verified exact; raw_fallback, observed 2026-08-15T19:53:52.723449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers