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Paper Citation Record · LEDGER

Prompts Blend Requirements and Solutions: From Intent to Implementation

As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2603.16348.

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

pith.paper-citation-record.v1
2603.16348 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:07:20.085073Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

32 of 32 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved31
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d154a5fd-ddd5-462d-a354-15032e96a987 · outbound

This paper cites Prompts Blend Requirements and Solutions: From Intent to Implementation.

Prompts Blend Requirements and Solutions: From Intent to Implementation Prompts Blend Requirements and Solutions: From Intent to Implementation

Reference 1

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source=pdf_text observed=2026-08-02T18:07:18.630039Z digest=sha256:89e19f1b63f6adc872c22f98f24b3dbe2c65374eb103bbd7c27809cc70f2fdae

Observation 3112e7a6-f0cb-4e7b-94d0-653522471403 · outbound

This paper cites Challenges of software requirements quality assurance and validation: A systematic literature review.IEEE Access, 9:137613–137634, 2021.

Prompts Blend Requirements and Solutions: From Intent to Implementation Challenges of software requirements quality assurance and validation: A systematic literature review.IEEE Access, 9:137613–137634, 2021

Reference 2

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source=pdf_text observed=2026-08-02T18:07:18.713674Z digest=sha256:055818acf3c2a955b4af8fbb45a3c90286731d838075f7e02a78e6d2fa96ee99

Observation 580eb45f-664b-4ad1-bff1-31ac25f11c08 · outbound

This paper cites Grounded copilot: How programmers interact with code-generating models.OOPSLA, 7:85–111, 2023.

Prompts Blend Requirements and Solutions: From Intent to Implementation Grounded copilot: How programmers interact with code-generating models.OOPSLA, 7:85–111, 2023

Reference 3

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source=pdf_text observed=2026-08-02T18:07:18.749836Z digest=sha256:1e00ecfed9bd0165e0b1d3282b4ca7c4e3ae6d985588435d62c6479ea583179d

Observation e118559a-d6e1-498c-82f7-c15f790a3649 · outbound

This paper cites an unresolved cited work.

Prompts Blend Requirements and Solutions: From Intent to Implementation Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-02T18:07:18.807274Z digest=sha256:446f21b8755aaeda442a4db20ee391aa1c3e84e0ac602db7808035c7ec92c3db

Observation d80a95bc-fb48-445d-abe4-518ac695e7f4 · outbound

This paper cites Vibe coding and the new prototyping playbook.IEEE Software, 42(6):12–16, 2025.

Prompts Blend Requirements and Solutions: From Intent to Implementation Vibe coding and the new prototyping playbook.IEEE Software, 42(6):12–16, 2025

Reference 5

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source=pdf_text observed=2026-08-02T18:07:18.850109Z digest=sha256:e10b839fa00d90955960c0aa787e46f713a2b5a3d30893b19fa24ab61197b039

Observation 0eda43d5-334e-49e2-86a2-5ffb28cc5285 · outbound

This paper cites Exploring prompts as mixed requirements and solutions artifacts.

Prompts Blend Requirements and Solutions: From Intent to Implementation Exploring prompts as mixed requirements and solutions artifacts

Reference 6

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source=pdf_text observed=2026-08-02T18:07:18.889324Z digest=sha256:71e461ef20a6015bead2e38c8751739fc92e4478e7334d4c95b61c3607170ec7

Observation f7ab7f8a-1aa9-4df0-9ad8-c4041a6dd421 · outbound

This paper cites Unleashing the potential of prompt engineering for large language models.

Prompts Blend Requirements and Solutions: From Intent to Implementation Unleashing the potential of prompt engineering for large language models

Reference 7

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source=pdf_text observed=2026-08-02T18:07:18.954923Z digest=sha256:b237f5671ce99f092b742216ce680de9c732372fd898dfa1303ad2e2a50e0021

Observation 01137720-781a-4ff2-acb5-1345c9b7ff6d · outbound

This paper cites Do prompt patterns affect code quality? a first empirical assessment of chatgpt-generated code.

Prompts Blend Requirements and Solutions: From Intent to Implementation Do prompt patterns affect code quality? a first empirical assessment of chatgpt-generated code

Reference 8

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source=pdf_text observed=2026-08-02T18:07:19.020408Z digest=sha256:6d27261fdd8994337c3b53a00959bdcac1742115415cce307784e6f3d5c54646

Observation 7f0d7085-d202-46ab-b381-e6384e23fe7d · outbound

This paper cites Exploring prompt patterns in ai-assisted code generation: Towards faster and more effective developer-ai collaboration.

Prompts Blend Requirements and Solutions: From Intent to Implementation Exploring prompt patterns in ai-assisted code generation: Towards faster and more effective developer-ai collaboration

Reference 9

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source=pdf_text observed=2026-08-02T18:07:19.068452Z digest=sha256:ababd780b77c86a294ca5ed416be1389918757a38caa422e14c529ef17eb6bee

Observation 38e87512-b4c1-4062-9a60-4bd1e817a449 · outbound

This paper cites Specifications are (preferably) executable.Software Engineering Journal, 7(5):323–334, 1992.

Prompts Blend Requirements and Solutions: From Intent to Implementation Specifications are (preferably) executable.Software Engineering Journal, 7(5):323–334, 1992

Reference 10

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source=pdf_text observed=2026-08-02T18:07:19.104935Z digest=sha256:3e47500bae40ab658ec40653ae805cc8b5cc886ff451e484d894066a55797d03

Observation 2ceefcf0-88b4-4e96-924b-ca52c46fcd3f · outbound

This paper cites Specifications are not (necessarily) executable.Software Engineering Journal, 4(6):330–339, 1989.

Prompts Blend Requirements and Solutions: From Intent to Implementation Specifications are not (necessarily) executable.Software Engineering Journal, 4(6):330–339, 1989

Reference 11

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source=pdf_text observed=2026-08-02T18:07:19.127360Z digest=sha256:6cb94619e48372f9be9e9e7b2f8f4ef5b4459b0802c3ea99ad0d3d7cae08ef3e

Observation a380eba4-4cbd-4df0-b9c9-e17421212f4e · outbound

This paper cites Prompt engineering for requirements engineering: A literature review and roadmap.

Prompts Blend Requirements and Solutions: From Intent to Implementation Prompt engineering for requirements engineering: A literature review and roadmap

Reference 12

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source=pdf_text observed=2026-08-02T18:07:19.168119Z digest=sha256:53c1efb08decd075f365f67595bd8bbd05392e4612f1a4a530402b5976b7362c

Observation 1fb26ac6-a5b2-4e98-ab21-ed51595ffa5d · outbound

This paper cites Understanding understanding and ambiguity in natural language.Procedia Computer Science, 169:209–225, 2020.

Prompts Blend Requirements and Solutions: From Intent to Implementation Understanding understanding and ambiguity in natural language.Procedia Computer Science, 169:209–225, 2020

Reference 13

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source=pdf_text observed=2026-08-02T18:07:19.219259Z digest=sha256:10d2df1fe1ffd7891b092d9fbc59ee3d53f59f1e5cbf42f1e377094dcb3a10ad

Observation f995c46b-4ab2-4b75-866a-aaf8323733e3 · outbound

This paper cites Detecting cross-domain ambiguity in requirements through natural language processing, a systematic literature review.

Prompts Blend Requirements and Solutions: From Intent to Implementation Detecting cross-domain ambiguity in requirements through natural language processing, a systematic literature review

Reference 14

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source=pdf_text observed=2026-08-02T18:07:19.257243Z digest=sha256:41658a39dfa48068a4f4ab7bcf3ce4c20adbafe38d068d3c6b0230e6f6599586

Observation c9cb567c-818d-49cb-bb78-5d51c955bb74 · outbound

This paper cites A vision on intentions in software engineering.

Prompts Blend Requirements and Solutions: From Intent to Implementation A vision on intentions in software engineering

Reference 15

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source=pdf_text observed=2026-08-02T18:07:19.293454Z digest=sha256:87e475859c10cd26faa595dbe234cd3a8435fedc4c3195a1f9dc3ef9116896f7

Observation 3fc33c7e-f0b3-44e5-a378-aa6810ff30b5 · outbound

This paper cites Vibe coding as a reconfiguration of intent mediation in software development: Definition, implications, and research agenda.

Prompts Blend Requirements and Solutions: From Intent to Implementation Vibe coding as a reconfiguration of intent mediation in software development: Definition, implications, and research agenda

Reference 16

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source=pdf_text observed=2026-08-02T18:07:19.352395Z digest=sha256:45aae2dc1c1bc5155d9051ce21413596f18f53ed39971c657122dae060e7372b

Observation 313d89ac-24f2-4483-a16f-3cbf2618e5d5 · outbound

This paper cites Nuseibeh, J.

Prompts Blend Requirements and Solutions: From Intent to Implementation Nuseibeh, J

Reference 17

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source=pdf_text observed=2026-08-02T18:07:19.425005Z digest=sha256:5bc01c7edcb58918154dd574b3bc1c40e8a081bcfc1a0ed49769e01608527978

Observation 5a6be47b-081b-4726-9b0b-8f647d7ad583 · outbound

This paper cites A review on vibe coding: Fundamentals, state-of-the-art, challenges and future directions.

Prompts Blend Requirements and Solutions: From Intent to Implementation A review on vibe coding: Fundamentals, state-of-the-art, challenges and future directions

Reference 18

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source=pdf_text observed=2026-08-02T18:07:19.464311Z digest=sha256:b62ac3a43e4ff5c9b23c1f281a5a0858f682049353cf5e80ad3c1169bdc292b9

Observation 15c155af-acbc-4dba-9e9e-0cba6f9389bd · outbound

This paper cites Prompt programming for large language models: Beyond the few-shot paradigm.

Prompts Blend Requirements and Solutions: From Intent to Implementation Prompt programming for large language models: Beyond the few-shot paradigm

Reference 19

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source=pdf_text observed=2026-08-02T18:07:19.499859Z digest=sha256:a529e7f96685649912150562705fa67f458242c2a43701f134412a4d9980a499

Observation 12227eb3-a63f-4782-bcfa-bc1587057759 · outbound

This paper cites A Self-Improving Coding Agent.

Prompts Blend Requirements and Solutions: From Intent to Implementation A Self-Improving Coding Agent

Reference 20

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source=pdf_text observed=2026-08-02T18:07:19.575335Z digest=sha256:5fec03dd551ebfd0d2795c8afe7d6b339dd2e81ac4a4f26bdbe7f0c02b2ba41c

Observation 4aad65a7-d423-4419-aa66-c0abe314cb51 · outbound

This paper cites Conversation Routines: A Prompt Engineering Framework for Task-Oriented Dialog Systems.

Prompts Blend Requirements and Solutions: From Intent to Implementation Conversation Routines: A Prompt Engineering Framework for Task-Oriented Dialog Systems

Reference 21

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source=pdf_text observed=2026-08-02T18:07:19.637550Z digest=sha256:ae27ad7000e43ffc8ddd85405e8c7d9f5c68299eafac7030e81817fd02aab018

Observation 1abde13f-48df-4bed-997c-1450ad10806a · outbound

This paper cites Prompt Engineering Guidelines for Using Large Language Models in Requirements Engineering.

Prompts Blend Requirements and Solutions: From Intent to Implementation Prompt Engineering Guidelines for Using Large Language Models in Requirements Engineering

Reference 22

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source=pdf_text observed=2026-08-02T18:07:19.697951Z digest=sha256:39a1e12776169b711cedc0c5e9b66cbb86aa58fedf8ace2b8a579589fe79d418

Observation f42e6af9-f3df-4b31-865f-89628dde51a5 · outbound

This paper cites An empirical evaluation of using large language models for automated unit test generation.TSE, 50(1):85–105, 2023.

Prompts Blend Requirements and Solutions: From Intent to Implementation An empirical evaluation of using large language models for automated unit test generation.TSE, 50(1):85–105, 2023

Reference 23

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source=pdf_text observed=2026-08-02T18:07:19.754214Z digest=sha256:0895734d6db61785a714c54ef821bbab0b88f4bdc6ec5c9bf52ed4271910f6a3

Observation c5c098c2-7799-421c-a29e-5795d92994b4 · outbound

This paper cites Using ai-based coding assistants in practice: State of affairs, perceptions, and ways forward.IST, 178:107610, 2025.

Prompts Blend Requirements and Solutions: From Intent to Implementation Using ai-based coding assistants in practice: State of affairs, perceptions, and ways forward.IST, 178:107610, 2025

Reference 24

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source=pdf_text observed=2026-08-02T18:07:19.787638Z digest=sha256:9be48174b02e07c39527a933b9d0c9b701a71d71c1bce2ebad81c4405d1003aa

Observation 8fbbcc2c-6f79-4b3f-99a0-f04c948c275e · outbound

This paper cites The fault in our stars: Quality assessment of code generation benchmarks.

Prompts Blend Requirements and Solutions: From Intent to Implementation The fault in our stars: Quality assessment of code generation benchmarks

Reference 25

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source=pdf_text observed=2026-08-02T18:07:19.837524Z digest=sha256:881ae80dddd601c7fec72aeb2d67ff767a40a3a53e96de6c0be5c771ef6784e3

Observation 5bab7466-b3f7-439d-86fc-5f8e6ff1be6b · outbound

This paper cites Expectation vs.

Prompts Blend Requirements and Solutions: From Intent to Implementation Expectation vs

Reference 26

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source=pdf_text observed=2026-08-02T18:07:19.889229Z digest=sha256:08b41d84844b91f40bb7858f07f609bcb13da1e284aa524b5b21b611a4a01f7d

Observation 4412d904-3f75-4278-9e49-514657ad94e8 · outbound

This paper cites Prompts as software engineering artifacts: A research agenda and preliminary findings.

Prompts Blend Requirements and Solutions: From Intent to Implementation Prompts as software engineering artifacts: A research agenda and preliminary findings

Reference 27

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T18:07:19.913042Z digest=sha256:7866598dd32fb83b2e8a4efd939e0557e2011b1658797f7a8bd78f226122c646

Observation 5aaf07ab-4cd8-4a4a-9415-c17f0bd9fec3 · outbound

This paper cites Prompting the future: Integrating generative llms and requirements engineering.

Prompts Blend Requirements and Solutions: From Intent to Implementation Prompting the future: Integrating generative llms and requirements engineering

Reference 28

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source=pdf_text observed=2026-08-02T18:07:19.956734Z digest=sha256:73327432e4b8d80f88d87ecc330e94a3759d81af06c7db7448afa4ff6d1bcb93

Observation 1fac65f2-9888-4fa0-9534-6428bc961d5b · outbound

This paper cites Ai agentic programming: A survey of techniques, challenges, and opportunities.arXiv preprint arXiv:2508.11126, 2025.

Prompts Blend Requirements and Solutions: From Intent to Implementation Ai agentic programming: A survey of techniques, challenges, and opportunities.arXiv preprint arXiv:2508.11126, 2025

Reference 29

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no resolver link, observed 2026-08-02T18:07:20.013952Z

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source=pdf_text observed=2026-08-02T18:07:20.013952Z digest=sha256:c657e786c9f8c192626cecc59313bd846148dcd8434c900c89564c63d13cb0ae

Observation 4a516eb9-dc6d-4b34-9972-9764985da994 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022.

Prompts Blend Requirements and Solutions: From Intent to Implementation Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022

Reference 30

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source=pdf_text observed=2026-08-02T18:07:20.046608Z digest=sha256:4220b0a2c459c06f50cf57d4ac12e5627e7590aaf608b79a5a9802c9ea7cb31d

Observation 00ef0e02-5157-4623-a216-9b996fbd72fb · outbound

This paper cites Devgpt: Studying developer-chatgpt conversations.

Prompts Blend Requirements and Solutions: From Intent to Implementation Devgpt: Studying developer-chatgpt conversations

Reference 31

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source=pdf_text observed=2026-08-02T18:07:20.085073Z digest=sha256:c2ebdc666836162848e5dc9648c0a11d631cb12e8661e19c2d0752387b224580

Observation d6c22dd5-6bbc-4464-943e-aacb8280cbbe · outbound

This paper cites an unresolved cited work.

Prompts Blend Requirements and Solutions: From Intent to Implementation Unresolved cited work

Reference 2026

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verified exact
doi, observed 2026-08-02T18:08:23.164753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-02T18:07:18.680619Z digest=sha256:dd893022b45fd1d7c1a557839db448f940a91cd5d82385393808e7077d60b36d

Pith citing papers

No inbound Pith citation observations are available.