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Paper Citation Record · LEDGER

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists

As of 11 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2501.10037.

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

pith.paper-citation-record.v1
2501.10037 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:26:31.612808Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation 84bf360b-7474-4c0a-bd08-5c8f75322659 · outbound

This paper cites Software engineering practices for scientific software de velopment: A systematic mapping study,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Software engineering practices for scientific software de velopment: A systematic mapping study,

Reference 1

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Observation 2a250831-17c1-4d73-aa48-d49c0f46a679 · outbound

This paper cites V aughan, Python Tools for Scientists: An Introduction to Using Anaconda, JupyterLab, and Python’s Scientific Libraries.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists V aughan, Python Tools for Scientists: An Introduction to Using Anaconda, JupyterLab, and Python’s Scientific Libraries

Reference 2

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Observation 245fa751-c294-4b77-bfd3-e2b63deacfd5 · outbound

This paper cites How do scientists develop and use scientific soft ware?,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists How do scientists develop and use scientific soft ware?,

Reference 3

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Observation b77624bb-24c1-4839-98f5-3f890232f72a · outbound

This paper cites A survey of the practice of computational s cience,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists A survey of the practice of computational s cience,

Reference 4

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Observation 447af4c9-e6bc-40fc-98bf-ff476910bbad · outbound

This paper cites Program comprehension du ring software maintenance and evolution,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Program comprehension du ring software maintenance and evolution,

Reference 5

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Observation 3c484684-c176-4919-89ee-a02dba258f78 · outbound

This paper cites Meas uring Pro- gram Comprehension: A Large-Scale Field Study with Profess ionals,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Meas uring Pro- gram Comprehension: A Large-Scale Field Study with Profess ionals,

Reference 6

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Observation 0586b614-d5c3-47a7-b202-18bb7c6c219f · outbound

This paper cites Reassessing Java Code Readability Models w ith a Human-Centered Approach,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Reassessing Java Code Readability Models w ith a Human-Centered Approach,

Reference 7

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Observation 8ba17462-3cf0-4cd2-be82-9ab33c3cb7f3 · outbound

This paper cites Linguistic antipatterns: what they are and how developers perceive them,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Linguistic antipatterns: what they are and how developers perceive them,

Reference 8

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Observation 486774c6-b099-48ae-8f63-f0e38c05a9db · outbound

This paper cites A Survey on Renamings of S oftware Entities,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists A Survey on Renamings of S oftware Entities,

Reference 9

Resolution
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Source-reported events for the cited work

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Observation 73697a66-f979-47bb-a2bd-37061403a47e · outbound

This paper cites On the Generation, Structure, and Semantics of Grammar Patterns in Source Code Identifiers.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists On the Generation, Structure, and Semantics of Grammar Patterns in Source Code Identifiers

Reference 10

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Observation 43a3af11-1066-400d-b1ea-7228b2738f51 · outbound

This paper cites What’s in a Name? A Study of Identifiers,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists What’s in a Name? A Study of Identifiers,

Reference 11

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Observation 531e5b73-5b61-473f-ae99-0e613ba5b803 · outbound

This paper cites A Systematic Literature Review on Empirical A nalysis of the Relationship Between Code Smells and Software Quality Attr ibutes,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists A Systematic Literature Review on Empirical A nalysis of the Relationship Between Code Smells and Software Quality Attr ibutes,

Reference 12

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Observation 0a5869ba-2df7-4037-a89b-e791874f636f · outbound

This paper cites An eye tracking study assessing source code r eadability rules for program comprehension,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists An eye tracking study assessing source code r eadability rules for program comprehension,

Reference 13

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Observation b3f3f943-8ea2-4be4-b34a-013add3d2009 · outbound

This paper cites 40 Y ears of Designi ng Code Comprehension Experiments: A Systematic Mapping Study,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists 40 Y ears of Designi ng Code Comprehension Experiments: A Systematic Mapping Study,

Reference 14

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Observation 259dd834-1ee6-479b-bd7b-61f6bf5f221e · outbound

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Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Exploration and Ex planation in Computational Notebooks,

Reference 15

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Observation 8e0ed542-3b1e-452a-a92e-02ba717e89d9 · outbound

This paper cites Scientists and software engineers: A tale of two cultures,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Scientists and software engineers: A tale of two cultures,

Reference 16

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Observation 1cfb261c-4e84-4a88-b1e5-7bf1a40e7ec8 · outbound

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Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Manag- ing Messes in Computational Notebooks,

Reference 17

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Observation c01670de-bff5-4acf-8a1b-971a9d112f28 · outbound

This paper cites A Comparison of Mac hine Learning Code Quality in Python Scripts and Jupyter Noteboo ks,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists A Comparison of Mac hine Learning Code Quality in Python Scripts and Jupyter Noteboo ks,

Reference 18

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Observation 82c0ef80-a83e-47f8-8733-01c8940e922f · outbound

This paper cites Understanding and improving the quality and reproducibility of Jupyter no tebooks,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Understanding and improving the quality and reproducibility of Jupyter no tebooks,

Reference 19

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This paper cites What’s Wrong with Computational Notebooks? Pain Points, N eeds, and Design Opportunities,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists What’s Wrong with Computational Notebooks? Pain Points, N eeds, and Design Opportunities,

Reference 20

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This paper cites Better code, better shari ng: on the need of analyzing jupyter notebooks,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Better code, better shari ng: on the need of analyzing jupyter notebooks,

Reference 21

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This paper cites A large- scale comparison of Python code in Jupyter notebooks and scr ipts,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists A large- scale comparison of Python code in Jupyter notebooks and scr ipts,

Reference 22

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This paper cites A Large-Scale Study About Quality and Reproducibility of Jupyter Noteboo ks,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists A Large-Scale Study About Quality and Reproducibility of Jupyter Noteboo ks,

Reference 23

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Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Qualtrics XM: The Leading Experience Management Soft ware

Reference 24

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Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Guidelines for conducting surveys in software engineering,

Reference 25

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Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Artifact Package

Reference 26

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Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Sampling in software engineeri ng research: a critical review and guidelines,

Reference 27

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This paper cites Wagner, D.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Wagner, D

Reference 28

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Observation 8c884bfb-2534-4f66-bdc9-a5b9ba3bd261 · outbound

This paper cites Descriptive compound identifier names improve so urce code comprehension,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Descriptive compound identifier names improve so urce code comprehension,

Reference 29

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Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists On t he Role of Computer Languages in Scientific Computing,

Reference 30

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Source-reported events for the cited work

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Observation edaf316f-424f-4b7f-9eac-16fe1aa05d29 · outbound

This paper cites Bug Analysis in Jupyter Notebook Projects: An Empirical St udy,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Bug Analysis in Jupyter Notebook Projects: An Empirical St udy,

Reference 31

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Source-reported events for the cited work

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Observation d039cd9f-fb7b-4034-849c-3547dd6a7dd9 · outbound

This paper cites Do Code Smells Impact the Effort of Different Maintenance Programm ing Ac- tivities?,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Do Code Smells Impact the Effort of Different Maintenance Programm ing Ac- tivities?,

Reference 32

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Source-reported events for the cited work

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Observation d8e91938-92e0-4431-8dcb-70b0941bfe60 · outbound

This paper cites The e ffect of poor source code lexicon and readability on developers’ cogniti ve load,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists The e ffect of poor source code lexicon and readability on developers’ cogniti ve load,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation f74aab48-6a53-4008-af14-b7d7256f7eb9 · outbound

This paper cites Ten simple rules for writing and sharing computational ana lyses in Jupyter Notebooks,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Ten simple rules for writing and sharing computational ana lyses in Jupyter Notebooks,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:26:31.772245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:26:31.591095Z digest=sha256:f1300f5fbd1310dbf0e549ef34ebca2821febb3578112780e69651293aafe2b9

Observation 340fbe37-c932-4536-89df-e8c2561ee7eb · outbound

This paper cites Future of software development with generative AI,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Future of software development with generative AI,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:26:31.754522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:26:31.595271Z digest=sha256:063dd0a611ab49c4428be34809a63d32a40b4792fad97b9f514341c07169d9b3

Observation b5399ba9-6063-41b8-8c73-936d565881c2 · outbound

This paper cites A Large-Scale Surv ey on the Usability of AI Programming Assistants: Successes and Chal lenges,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists A Large-Scale Surv ey on the Usability of AI Programming Assistants: Successes and Chal lenges,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:26:31.737223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:26:31.600241Z digest=sha256:cafd9f61782faf37359bd2645737028bf514aa350613bf027874ab4c6dd6c90c

Observation 6e4bd38c-e24e-4ae9-9b90-c0ae6ef2419f · outbound

This paper cites Assessing the Readabi lity of ChatGPT Code Snippet Recommendations: A Comparative Study ,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Assessing the Readabi lity of ChatGPT Code Snippet Recommendations: A Comparative Study ,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:26:31.719740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:26:31.604220Z digest=sha256:fa07a08733a744269cbcb0654dac2551ab8a5d17060c0499b5a331096d0da47a

Observation 84452f55-f4c5-4ac6-b243-ecc0f3ccaa23 · outbound

This paper cites Q uality Assessment of ChatGPT Generated Code and their Use by Develo pers,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Q uality Assessment of ChatGPT Generated Code and their Use by Develo pers,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:26:31.701929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:26:31.608659Z digest=sha256:d79f0806127f8c1e6f140b6ba2b8e137cacffdc6020b30e65b616f0820ace056

Observation 45515f29-ab40-43d1-bb2a-a1391618bf4e · outbound

This paper cites Refining ChatGPT-Generated Code: Characteri zing and Mitigating Code Quality Issues,.

Exploring Code Comprehension in Scientific Programming: Preliminary Insights from Research Scientists Refining ChatGPT-Generated Code: Characteri zing and Mitigating Code Quality Issues,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:26:31.685338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:26:31.612808Z digest=sha256:069dd54e14f857e46147a0a7b7255c4e4e16fd04bdd497b4e27cc2d5aca260de

Pith citing papers

No inbound Pith citation observations are available.