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Paper Citation Record · LEDGER

Prompts Blend Requirements and Solutions: From Intent to Implementation

As of 7 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 2026-08-07T06:34:17.273281+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

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  • 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:ff721ca12d8a6ca8ee108ddd0a99ddf75007fb85e6289060d03a4be75ecb14f6

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=sha256:18910fef934e60060634008807b4dc89dda756a23232319cc73002495f5f2304

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=sha256:81509e232f7e89ec3ac9b5676e7faa64d6e097b42ff2b337fc4465865798b99f

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=sha256:19ad16346b3384b70da0817404d2f3addc81e86e9265f8088a5dc03d06a3053e

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=sha256:6b6a5db719c5888ffd32aa64a087faae99eb4ca6ab9f16b6c88355d5c22d37a8

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:e490da8a991a7bd9fd4d7da534576b2945c2566567a0464a849ac293a9df395e

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=sha256:9b76b27b7cb2b01596f869972a5c4b4fb2d9c6682113f9da29eaf1bc8aee94bf

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=sha256:3def96eecdb4ac6449a0781adb430580b28cc44b2450373ed83846ef9383cc69

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=sha256:943c091d6468b92b5c59d78d1bcdbcd26a32c8c8493beeda51f25983d7525ff4

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=sha256:94bdb2c60fd06d193bb65cb9edb30291036e4213c90848d904621f0763fdad4d

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=sha256:396e2f943cba424f14be9908dc94006d8c9857ff90e3886541f7a675ed3f4b2b

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:c16e7582eb938e6a17584a6a699ef99ce9ad907f2a87adc4cb6f9c7f25b21a8c

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:bff45804f94a41e0fe4f9c1b221d0407c65947cc450d89809cbefdfaae1cffb0

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=sha256:8cba133d57cf5af37c08868b917601cd8989186637963f5ca32196504c4cddff

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=sha256:8b49b77303470a60b80ab3877522bc638103ae08adb667f026628418be9b61f3

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:bc5e6fd4b7ba2416750114b25d3571f59a3bef012763be556f589e71f7fd28e6

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:c9346f57c7e41d32b39030f5dca6c890228b8c1088e1faf6a13d1de559fb3375

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=sha256:1da2b1b2ba87bbe06273aa1d4809a02dec38016e58fa0607e0de7785c3c35a2d

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=sha256:8ae3f12998d6371845894825ca9710df6dcfbffcae6d3ba41d4c891ab72bc539

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=sha256:9951ae4e2671df4d7c02c8414b22a0d85f3e0eefd2d300e76f367994072cc248

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:b767dc308c091fefb145bd9eadf8941dfa4e39f230625a763f909f3faf0c0166

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=sha256:197210a07a674f267416bc20d31407d90cb43adba89d01dae3d0b5e41fc5a03f

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:cd2cd058a6583241f25ddd6f37cbe83f29805b41a8566e5ff9278742f13302ef

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=sha256:83013bee17c3b2dba90c0d59d6f342e721983364cfefd43f2175a90819bc33ff

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=sha256:2dad595fa634242c3374b1fac743dd79b978fb2992c856fae669b5112a2958a5

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=sha256:26ca82c1a334f00a602d7c429c03cb0239010b4c98bc2abb19bf4c9466c82e7d

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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source=pdf_text observed=2026-08-02T18:07:19.913042Z digest=sha256:01ab47b11452bd9ad3d2bba3d8e64633541173aad81c1c76282264e8d92358c4

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=sha256:9e6819f66d5e878767fb2de80cf6c78551061a6a92ba932f5a57bf8aef4ad4e1

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:f8d9708fbd6c4ee00e6f8cf1cab5a3a4521e46b69cfa88dcdd381332d058ac3d

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=sha256:0d8de2626109c639a846d555fcf767c2cec16fd6c5021de5376939516571a5de

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:c1ecfef6d239e9b43ff2631d381e213e6303bc135f2e400b05371af17253cbdd

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-02T18:07:18.680619Z digest=sha256:22d4e0a6cf80b76c837c89b8055633ea0937fd666531e3e4a75054578411dc6a

Pith citing papers

No inbound Pith citation observations are available.