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Paper Citation Record · LEDGER

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering

As of 17 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2501.06837.

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

pith.paper-citation-record.v1
2501.06837 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:53:54.938567Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:41:44.896555Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T05:30:23.456663Z

Reference resolution

32 of 32 outbound references displayed

  • verified exact2
  • verified fuzzy29
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
pith, observed 2026-08-10T05:30:23.456663Z

Outbound references

Observation 8545df2b-5a67-4330-b3f5-114f1a15195b · outbound

This paper cites Quality in web engineering.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Quality in web engineering

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.449840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.774287Z digest=sha256:7bfc2e72cc192918fc371ebddebae6bc368d9fb1e5d5d49b9299f01f514082d3

Observation 10f5080d-d628-4f7d-b201-f806b9591156 · outbound

This paper cites Applications of automated model’s extraction in enterprise systems.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Applications of automated model’s extraction in enterprise systems

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.436247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.779828Z digest=sha256:59ed46ab5a9771a960f8d4afeca7b35b7a3dc8335c6613dd5a199c465b666a6d

Observation 80d50939-7f88-447d-ab1a-a529c8b081d1 · outbound

This paper cites Revolutionizing software testing: The impact of AI, ML, and IoT.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Revolutionizing software testing: The impact of AI, ML, and IoT

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.421575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.785212Z digest=sha256:cfad65860d1397dcb3cd98d7458c686331143948d945a087afd89d717d04bc65

Observation 0152a90b-4504-4fd4-b8ab-a2794a65b445 · outbound

This paper cites Artificial intelligence in software testing.International Journal of Innovative Science and Research Technology, pages 616–619, 2024.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Artificial intelligence in software testing.International Journal of Innovative Science and Research Technology, pages 616–619, 2024

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.407518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.789753Z digest=sha256:fb2405bfe27a82c69ba335918354341332c0155b79eea77e71ad431a25884490

Observation 156785d4-7928-40f0-97a0-f80e3269d37e · outbound

This paper cites An empirical study to compare three web test automation approaches: NLP-based, programmable, and capture&replay.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering An empirical study to compare three web test automation approaches: NLP-based, programmable, and capture&replay

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.395648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.794818Z digest=sha256:51226f1334a6c05b1e9366a783896d6cb43c215600d738ee78e3a68c79140f4b

Observation c5548010-a699-4611-ab02-86a3f4f769e0 · outbound

This paper cites AI-powered software testing: The impact of large language models on testing methodologies.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering AI-powered software testing: The impact of large language models on testing methodologies

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.383984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.799311Z digest=sha256:a40cc63277f11e94d182b7e512c093bf2d81b6ef841d31be2dc3b0e673b04355

Observation ccc77aab-e274-4b44-b69c-6cdf7aeddbef · outbound

This paper cites Software testing in the era of AI: Leveraging machine learning and automation for efficient quality assurance.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Software testing in the era of AI: Leveraging machine learning and automation for efficient quality assurance

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.371720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.804233Z digest=sha256:2868a8717f6b31be64da1522106f10f286b50861d02ec1c2d054c456ab65c73a

Observation b2e893d8-a866-4483-b82b-8485c2d6f928 · outbound

This paper cites A comprehensive enterprise system metamodel for quality assurance.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering A comprehensive enterprise system metamodel for quality assurance

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.358922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.808736Z digest=sha256:86ebd63106ac91f098f47ffdf23aa1172182e0c2258723a1bff5ee17a17a3941

Observation ba9f96e7-97ed-48fc-8169-1fd21fdf918c · outbound

This paper cites Natural language processing-based software testing: A systematic literature review.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Natural language processing-based software testing: A systematic literature review

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.346469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.812692Z digest=sha256:a2d0cc63235ff237204894a7e6d409f3202938070e2d9fe168706b4e0ce5e36c

Observation 13f89742-926b-4864-9683-e93e9a1cdb42 · outbound

This paper cites Large language models for software engineering: Survey and open problems.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Large language models for software engineering: Survey and open problems

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.332646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.817295Z digest=sha256:7f31d6627f9fae280aab16fabe7d76fbb34f44bb8bf9d46255d62f24f14f8235

Observation 7272ae3b-e2d2-4efc-8b61-7f416c3a9dc4 · outbound

This paper cites Software testing with large language models: Survey, landscape, and vision.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Software testing with large language models: Survey, landscape, and vision

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.319169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.822322Z digest=sha256:f4a3baaff017cdb8090bb31891bcee6b3bf9246d07059a86ba5f2016dfeea607

Observation 758a5263-393f-4360-84c8-0c99dc1a97c5 · outbound

This paper cites A conceptual framework for quality assurance of LLM-based socio-critical systems.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering A conceptual framework for quality assurance of LLM-based socio-critical systems

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.306016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.826727Z digest=sha256:15fc2971d0cc075102fab2d35588af026d562e47473346adaad922a75f632a28

Observation a8af9da3-0932-45e9-a8dd-45acadf37fdf · outbound

This paper cites LLM for test script generation and migration: Challenges, capabilities, and opportunities.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering LLM for test script generation and migration: Challenges, capabilities, and opportunities

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.293309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.832200Z digest=sha256:4a7cacc6e1782cf6cad83ef6f8a1e2d248229f06db85751d7eccbb5be8f6e302

Observation 43ed1991-810a-4ad1-8795-0302709dbc77 · outbound

This paper cites A Case Study on Test Case Construction with Large Language Models: Unveiling Practical Insights and Challenges.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering A Case Study on Test Case Construction with Large Language Models: Unveiling Practical Insights and Challenges

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-10T20:53:55.009100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.836711Z digest=sha256:cb031f03b8b0bac45985409ee3c13624584c729106dca66fa358674d15ac7521

Observation 7673af47-9906-4aad-a64c-84d30b1b3fa6 · outbound

This paper cites Automated test case generation from requirements: A systematic literature review.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Automated test case generation from requirements: A systematic literature review

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.279526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.842317Z digest=sha256:8bbd8cfc774e75fd18c6eb6cb93b421f395118046cfbccc0ca1abf6a1090f145

Observation 237816ab-3137-488e-8fa0-a1c6e617ccba · outbound

This paper cites Requirement-based automated test case generation: Systematic literature review.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Requirement-based automated test case generation: Systematic literature review

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.267375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.846700Z digest=sha256:c128e78c21ad9d1741d07ac4f58d75056ff6e4810fce73efc1bc19a765e6a0fa

Observation c8fcf0e9-995c-4095-8c4d-438321a28bb3 · outbound

This paper cites A semi-automated approach for requirement-based early validation of flight control platforms.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering A semi-automated approach for requirement-based early validation of flight control platforms

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.254773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.850641Z digest=sha256:ae1cb3075ba03126cdf677e506c734afe8ad3988f83a9f46cefe349551f4ac0e

Observation 90b5bcda-3d21-46ce-b8f5-6cf6e0b35ed8 · outbound

This paper cites Functional test generation from ui test scenarios using reinforcement learning for android applications.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Functional test generation from ui test scenarios using reinforcement learning for android applications

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.236530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.854867Z digest=sha256:3cda93ba31b67acb992707e044545cdd59c2fc9c564c79c4d1620b1f52545c3b

Observation f52f5a7b-711b-4bc6-ad4c-c6b023d142f1 · outbound

This paper cites Web program testing using selenium python: Best practices and effective approaches.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Web program testing using selenium python: Best practices and effective approaches

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.221395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.858469Z digest=sha256:bd69ae5360f840fde292547ca246c76f3300d350fb21b8f880b6f17a854dbde9

Observation 6246fa36-da55-4e3a-9dc5-1bdd49173bba · outbound

This paper cites Automated testing of web project functionality with using of error propagation analysis.Computer Systems and Information Technologies, 2023.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Automated testing of web project functionality with using of error propagation analysis.Computer Systems and Information Technologies, 2023

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.204073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.862579Z digest=sha256:eeec4f899de4752fbc26ad61440dc2824708308c24f8dada1f9fcaac81384464

Observation 78c41c34-3e02-4a9b-baab-9abf6bcae529 · outbound

This paper cites Automated functional testing pada api menggunakan keyword driven framework.Journal of Informatics and Communication Technology, 2021.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Automated functional testing pada api menggunakan keyword driven framework.Journal of Informatics and Communication Technology, 2021

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.187442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.867049Z digest=sha256:436a1ba30ecf7df66cb9babd91ef14e92edfbba8ba7f159319950a7b14c996ad

Observation fb2fbf5a-aa89-45b7-82c1-cd63b788adc7 · outbound

This paper cites Automating test oracles from restricted natural language agile requirements.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Automating test oracles from restricted natural language agile requirements

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.171679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.873830Z digest=sha256:27915fce3d16fabeb2dcb7a1c933bf4c17a3d517f120615d5cea1a2238d2f98b

Observation b209b59f-a3bd-4d6f-9304-aa9807ad1066 · outbound

This paper cites A bert-based transfer learning approach to text classification on software requirements specifications.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering A bert-based transfer learning approach to text classification on software requirements specifications

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.155995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.878239Z digest=sha256:b9dbe0fe964949ddc64654e111b352161d7f15ca40be842fa2169311bf2ee580

Observation de7aaeee-bbf9-4349-b23e-55e25c8b03b7 · outbound

This paper cites User stories and natural language processing: A systematic literature review.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering User stories and natural language processing: A systematic literature review

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.139390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.883285Z digest=sha256:dc0a181f3782bff8d109bdeb746fe90749a50911df5e429a5c249d3c02022e65

Observation 8579411f-e88d-4a62-869b-6f3a46c9c299 · outbound

This paper cites MuFBDTester: A mutation-based test sequence generator for FBD programs implementing nuclear power plant software.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering MuFBDTester: A mutation-based test sequence generator for FBD programs implementing nuclear power plant software

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.119965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.891698Z digest=sha256:477543aa652dd14abfec594c10853e19f6984b48030d923e09ff06a1cc51401a

Observation 63c8cd5e-721c-4f14-81c9-b1cddd4cf88a · outbound

This paper cites Software test case generation using natural language processing (NLP): A systematic literature review.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Software test case generation using natural language processing (NLP): A systematic literature review

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.101900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.900518Z digest=sha256:ba93ccdbf43e7a801b06f0e9522044b02a9546cb35e4e550514f11bd65ea03b9

Observation 58ddc8e0-d0ca-4d6a-883d-d82cd397ea39 · outbound

This paper cites An empirical study to compare three web test automation approaches: NLP-based, programmable, and capture&replay.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering An empirical study to compare three web test automation approaches: NLP-based, programmable, and capture&replay

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.086539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.907197Z digest=sha256:46d1e05f84f35f328b837c77d257c1ef5aa6eb4dcfaa36959512832334e7c2e8

Observation e2e0157a-9029-40eb-b89b-f1d0c0d586d6 · outbound

This paper cites an unresolved cited work.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-10T20:53:55.069838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.912006Z digest=sha256:7c5c28732726156a7e7ee0df378312b6de87ba04aa004951705a2ce2cb70da3d

Observation 7ce05371-c954-4652-95d4-7d1e2330e11c · outbound

This paper cites Chen, Gunvant Chaudhari, Thienkhai Vu, Youngho Seo, Jared Narvid, and Jae Ho Sohn.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Chen, Gunvant Chaudhari, Thienkhai Vu, Youngho Seo, Jared Narvid, and Jae Ho Sohn

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.055517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.916748Z digest=sha256:37deca8ad23d974ce19d6b5823cd0ce0061499f72d973a2ed09611efbdaa3f68

Observation cadceeee-22fa-4c09-92b4-6ee8ac920e0c · outbound

This paper cites Natural language processing for assessing quality indicators in free-text colonoscopy and pathology reports: Development and usability study.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Natural language processing for assessing quality indicators in free-text colonoscopy and pathology reports: Development and usability study

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.041992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.922825Z digest=sha256:bd779b59340a860b480ab793a5b752373c69e3a0563d666e21822097ea324c2a

Observation f22bc29c-73aa-44de-914b-f792cd863043 · outbound

This paper cites Tignanelli, Greg Silverman, Elizabeth Lindemann, A.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering Tignanelli, Greg Silverman, Elizabeth Lindemann, A

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:55.027430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.933959Z digest=sha256:27d899b3b7b97193c0a29a0c1f41cff340fc6e10b6747ccea106c0c4fdf837d7

Observation b64b9294-45de-46d1-b87c-9c319ef92fb4 · outbound

This paper cites AEON: A Method for Automatic Evaluation of NLP Test Cases.

An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering AEON: A Method for Automatic Evaluation of NLP Test Cases

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-10T20:53:54.987738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T20:53:54.938567Z digest=sha256:de1cba94a1e8321f2b3ad90a1565504790cfa17a08cb883c1a2d28384eb1d3dc

Pith citing papers

Observation 721e627e-7981-4793-8f3c-776a7b4b92af · inbound

AI-Driven Tools in Modern Software Quality Assurance: An Assessment of Benefits, Challenges, and Future Directions cites this paper.

AI-Driven Tools in Modern Software Quality Assurance: An Assessment of Benefits, Challenges, and Future Directions An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering

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local_arxiv, observed 2026-08-06T23:41:46.899446Z

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