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Paper Citation Record · LEDGER

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

As of 20 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 0 inbound Pith citation observations for arXiv:2506.14640.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.14640 v1

Coverage vector

measured 73 of 73 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:53:52.376098Z

measured 73 of 73 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

73 of 73 outbound references displayed

  • verified exact8
  • verified fuzzy25
  • unresolved30
  • parse uncertain0
  • malformed identifier5
  • metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8b188ece-a4c1-44e7-a3e3-3babe67820cc · outbound

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)

Reference 1

Resolution
verified exact
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Source-reported events for the cited work

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Observation f87b2adc-853f-4de8-bea2-2a1e644bd25e · outbound

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

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:53:55.701329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a5e1890b-71ae-49e2-9537-4173a5ab75f8 · outbound

This paper cites URL http://purl.

Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey URL http://purl

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9679f72f-d56b-41ed-9cd2-a8dead4f7b08 · outbound

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

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 2f21fe37-0e20-4e1d-ac18-aa1168d38e88 · outbound

This paper cites In: 2023 Innovations in Intelligent Systems and Applications Conference (ASYU).

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)

Reference 6

Resolution
malformed identifier
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7c79239b-be53-40e5-b21c-6edc276adc87 · outbound

This paper cites Springer Science & Business Media (2006).

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)

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 8bd649d4-69d1-409b-be75-23feba95f419 · outbound

This paper cites In: Companion Proceedings of the 30th Interna- tional Conference on Intelligent User Interfaces.

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

Reference 8

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metadata mismatch
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c16c2a95-36ee-4167-bad7-a35236b8d4b1 · 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 9

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation bdebfdf8-c25a-48c5-8cb9-9795f7f2795b · outbound

This paper cites In: 2022 IEEE Aerospace Conference (AERO).

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)

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e9f33e0c-5dee-453f-964b-5ff041064a7b · outbound

This paper cites In: Proceedings of the 3rd ACM/IEEE International Conference on Automation of Software 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 In: Proceedings of the 3rd ACM/IEEE International Conference on Automation of Software Test

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b0e1d1bb-0721-4199-b5d1-2576d1af532e · outbound

This paper cites In: Early Research Achievements (ERA).

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)

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1c5ee9e8-bc8f-4875-aeb8-c1748bf0200a · outbound

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

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 15c0cb5e-b3a2-4400-972d-fe6706e94e5a · outbound

This paper cites International Journal on Software Tools for Technology Transfer16, 559–568 (2014).

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)

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c805eb69-3ca6-4890-94ee-efa6372ed288 · outbound

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

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 57943720-0c87-45d1-9d4b-ff488437c286 · outbound

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]

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 993a0748-5ba8-4b03-9dca-1f8331f355d4 · outbound

This paper cites In: 2025 IEEE Conference on Software Testing, Verification and Validation (ICST).

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)

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 413c5909-d285-4655-94fe-02302fa306c0 · outbound

This paper cites In: 2023 5th Novel Intelligent and Leading Emerging Sciences Conference (NILES).

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)

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a9cbe145-67fb-46b5-a22b-452d14df1b55 · 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 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b1692c56-09ef-408e-82fa-3d0a25b75bf3 · outbound

This paper cites In: 2022 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: 2022 IEEE International Conference On Artificial Intelligence Testing (AITest)

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9855ebe3-4c2d-4a8a-b8d2-94204be2b396 · outbound

This paper cites In: 2023 International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT).

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)

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation eaf3e91c-d072-4299-80ad-9fc85f61d2e4 · outbound

This paper cites In: 2024 5th IEEE Global Conference for Advancement in Technology (GCAT).

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)

Reference 23

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 24fd5479-f2aa-4139-affb-b7c3979063a7 · outbound

This paper cites In: Proceedings of the 1st ACM SIGSOFT International Workshop on Languages and Tools for Next-Generation Testing.

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

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6e4cc849-32e5-46cc-b61c-a48a412ad56f · outbound

This paper cites In: Conceptual Modeling: 37th International Conference, ER 2018, Xi’an, China, October 22–25, 2018, Proceedings 37.

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

Reference 25

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 30f854f5-4695-45b7-8a4c-7c578e03bb4a · outbound

This paper cites In: 2025 IEEE Interna- tional Conference on Software Testing, Verification and Validation Workshops (ICSTW).

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)

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 757349b7-b246-4ec8-b786-1286c473534e · outbound

This paper cites In: 2024 IEEE Frontiers in Education Conference (FIE).

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)

Reference 27

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fc5a6816-62a2-49c7-8821-4dc4c70137ba · outbound

This paper cites In: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of 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 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Reference 28

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 00ff6c4f-038d-4f27-b118-aafe0856df6a · outbound

This paper cites In: 2024 International Telecommunications Conference The ai4st taxonomy and its use 13 (ITC-Egypt).

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)

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e2d2ce3a-6682-4037-9fee-2b7a173c5406 · outbound

This paper cites TOGLL: Correct and Strong Test Oracle Generation with LLMs.

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

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f242a104-225b-4142-866b-240c531bbbcb · 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 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Reference 32

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a67932e1-e903-4d64-bbe3-7298a4e055f2 · outbound

This paper cites In: 2025 Fifth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT).

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)

Reference 33

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c5a1df18-7d3a-4f2e-b7c6-645db54e6081 · outbound

This paper cites In: 2020 10th International Con- ference on Cloud Computing, Data Science & Engineering (Confluence).

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)

Reference 34

Resolution
unresolved
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Unavailable: canonical work link unavailable.

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This paper cites In: Proceedings of the 5th ACM/IEEE International Conference on Automation of Software Test (AST 2024).

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)

Reference 35

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Observation 5c75a38b-ae0b-4624-a186-b7ad1e578d52 · outbound

This paper cites In: Proceedings of the XXIII Brazilian Symposium on Software Quality.

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

Reference 36

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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

Reference 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 W3C recommen- dation 10(10), 2004 (2004)

Reference 38

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This paper cites In: 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).

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)

Reference 39

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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)

Reference 40

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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)

Reference 41

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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 42

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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)

Reference 43

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Observation 9578cf0f-2e6a-4360-ae79-d28e8b99ac90 · outbound

This paper cites https://doi.org/10.1109/AST66626.2025.00008, http://arxiv.org/abs/2502.

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

Reference 44

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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)

Reference 45

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f14531b9-a8d5-40df-8bca-43804508dc05 · outbound

This paper cites In: 2011 IEEE Third International Conference on Cloud Computing Technology and Science.

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

Reference 46

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Observation 06194908-203d-4954-a02a-ae7642e70a53 · outbound

This paper cites Communications of the ACM55(11), 12–12 (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 Communications of the ACM55(11), 12–12 (2012)

Reference 47

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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)

Reference 48

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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

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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

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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 com/schieferdecker/ai4stpaper

Reference 52

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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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 12th International Workshop on Automating TEST Case Design, Selection, and Evaluation

Reference 54

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

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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: 29th Annual International Computer Software and Application Conference (COMPSAC), Edinburgh, UK

Reference 55

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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 Ap- plied Ontology 12(1), 59–90 (2017)

Reference 56

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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

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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: Central European conference on information and intelligent systems

Reference 59

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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Unavailable: canonical work link unavailable.

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Reference 61

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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Unavailable: canonical work link unavailable.

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

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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 Software testing, verification and reliability22(5), 297–312 (2012)

Reference 64

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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Unavailable: canonical work link unavailable.

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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

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T19:53:52.355685Z digest=sha256:219adf19d0d8d0d203f571858a28965c356147b37a5cde9d42518d77d8873186

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T19:53:52.359736Z digest=sha256:c43f30e21f694b0398385f5b0e834edfbc85267820166258800ef67933ce0467

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T19:53:52.363918Z digest=sha256:66820215fe1dae69feacf494176c94a97b33c5fe5f99a07d893c44ed0a82371a

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T19:53:52.372165Z digest=sha256:be453c97b6c52a3aa77e7bf005515ce28012476268b117658433a97f9d3e54a6

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.

source=pdf_text observed=2026-08-15T19:53:52.376098Z digest=sha256:af9fe01ea3d11aec6f5c5cd23c010e64902d4d4b650cdf287cadd58ae2e8811d

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.

source=pdf_text observed=2026-08-15T19:53:52.168849Z digest=sha256:06a12e08b6b913eab9752156bf3cba3a1a1a20d36d6f671914029fde2cd8d502

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T19:53:52.368040Z digest=sha256:bb2a211156fe13e42a2490e967b1b6c031c7a24156c7b42a991f1349bb240d51

Pith citing papers

No inbound Pith citation observations are available.