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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 13 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 2026-08-12T06:34:41.77262+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 2026-08-12T06:34:41.77262+00:00.

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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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.779828Z digest=sha256:a8862dda4fe02cdca0e784b5b2a342436569778a3e9c83ae44c55bef455ebcde

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.785212Z digest=sha256:eb97218fc5b3c58015d5334541e683cb364074d482f73cd44dd7f04a1e69301b

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.789753Z digest=sha256:3d6cffcac4610be7f85685f59bf79f636787408a2cfe8b4c7fb4d4b047d0b05b

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.794818Z digest=sha256:133d25bf551765a48a2ca29e1c81603c6070c665404d48055ef0533e61e83117

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.799311Z digest=sha256:121c01f479656d2393109461daad01326ba09a129e4a88f5de7619e91f127fbb

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.804233Z digest=sha256:de5b1c4d52ac17321c4c1a88a9879d4a239a97272a7f651f99e609421e16b8fd

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.808736Z digest=sha256:50ea552e7945edc83839dbe7d494ae5c7e7f5a2b9db12028cb6325bdc028f653

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.812692Z digest=sha256:2915bba5c5cc99b2edb1a99095374b072b607adf2a9ba81ab74e774425941149

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.817295Z digest=sha256:e023db3735c65ebaa5177462bb9a890353faa3e18d448591e5fd2604f195b49e

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.822322Z digest=sha256:aa90e8dd65476301b101009b0ea030ec2da00aed8f389b8c12d614e9118f86f2

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.826727Z digest=sha256:80501a644ae29b0e69fb618526871e466eb163e7d010a4d0a6bc526ed977d0a3

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.832200Z digest=sha256:ed4ceecd8b3fee68e334376bcaaba9277205409f0be282a904a3e82f9bac35ce

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.836711Z digest=sha256:ab3db879b67c3d11d29798739e585c761a474416b5cd4324f9d227ce8d5cfc85

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.842317Z digest=sha256:bc4bd1b62af19bb60a0ae5c7431f285b06543b79f0dfaf0ceb1d6a0998ac47be

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.846700Z digest=sha256:620825ebd3e57e53c4f40ba4de606267655c11601db464e2dab312d1c3882b1d

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.850641Z digest=sha256:fba35678c8c7903fee949bbff142fffb229aceedc3ab2ff9730148cfd42ebacf

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.854867Z digest=sha256:c43c49063dc4546907e41d813703e47b3db2de2567239bd112d104d8b86dc081

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.858469Z digest=sha256:efbcfced9f361f48e21b72cfc9c15df24d1f01dedbf2947da77600a9baedfaef

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.862579Z digest=sha256:913094124940ccd64e02ee56cbe7dbc8f4ee992656e1147fbc009ab9b98e3423

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.867049Z digest=sha256:63ed89197ee0233a52721c621fd25512df0bc3fc1a17db4b6a9b1df967fa92ce

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.873830Z digest=sha256:96924bc5a3a1b68c3a78a14a1f64fb63c90532518389fac5abedaeecac0f05df

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.878239Z digest=sha256:cfc2321ca41b8610d5a2ed8c5348e65c081f21bf507797848edf19b78b969d3d

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.883285Z digest=sha256:9c705de93692709b67a168a93033d7d10288261b1f919030cb352247f07b9f99

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.891698Z digest=sha256:82aad71adf484f3b99883e87008b2805b3c13e7713b59bb56ad91204d0e58b1e

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.900518Z digest=sha256:939df24e74a4ad04ee286991b5b04ea428f7bb7edba03c7b765df9947ccc0693

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.907197Z digest=sha256:65e92baeba606fd545371669d99d361368a76d1b7559d7280c35197193a5d233

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.912006Z digest=sha256:43a84fbcf0727f7fd916783b204f2fe8b8f3f29f9bc2cfc0fae8c273073d5233

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.916748Z digest=sha256:b819f62a0bd04e9cfa196d040f117d4de46263c389470e689eda08852f7e76d1

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.922825Z digest=sha256:8d995d98ab3201608a00514e743b12a670d8a587967fdf1cd297db1ee731807f

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.933959Z digest=sha256:10da9f68e630bbb5557e4ed2bc300b4b9d1ea5c5cb99a345634d5fa979ffee01

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T20:53:54.938567Z digest=sha256:4b80753bd3a11abf8a4010ed19e17a010d9de3477155f02931561270f764a3f0

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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