Paper Citation Record · LEDGER

An Empirical Study on the Potential of LLMs in Automated Software Refactoring

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2411.04444.

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

pith.paper-citation-record.v1
2411.04444 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:09:55.746914Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

5
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c297a957-303d-4f15-8de6-54796ce7ddd1 · inbound

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards cites this paper.

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 151

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:46:37.100812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3cb4f36c-ab2a-4dfb-8538-e7d80b05a1d2 · inbound

Teaching Code Refactoring Using LLMs cites this paper.

Teaching Code Refactoring Using LLMs An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T21:09:55.746914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61af056b-3f3d-46d7-8542-c9ac82d77631 · inbound

AI-Assisted Unit Test Writing and Test-Driven Code Refactoring: A Case Study cites this paper.

AI-Assisted Unit Test Writing and Test-Driven Code Refactoring: A Case Study An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T18:53:08.485569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 34854e89-b3ea-4b51-b2e3-53d5e991fc8b · inbound

Foundation Models as Oracles for Refactoring Correctness Detection cites this paper.

Foundation Models as Oracles for Refactoring Correctness Detection An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:00:36.144612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 73c1f906-bbbb-4035-b40f-13ec521ec08e · inbound

Foundation Models as Oracles for Refactoring Correctness Detection cites this paper.

Foundation Models as Oracles for Refactoring Correctness Detection An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-07-04T01:49:21.451879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6c4dc071-bef3-44ad-9172-6fe6080751bb · inbound

Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions cites this paper.

Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:21:08.430213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7d1a984c-ddd1-4f89-a860-d7859b98835c · inbound

Given, When, Then, Again: Mining Subscenario Refactoring Candidates in Behaviour-Driven Test Suites with ML Classifiers and LLM-Judge Baselines cites this paper.

Given, When, Then, Again: Mining Subscenario Refactoring Candidates in Behaviour-Driven Test Suites with ML Classifiers and LLM-Judge Baselines An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T01:33:26.896796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9f69cb05-98f3-477b-b24e-46cacda0ea41 · inbound

LLM-Based Porting of Optimized C++ to CUDA Through Deoptimization and Reoptimization cites this paper.

LLM-Based Porting of Optimized C++ to CUDA Through Deoptimization and Reoptimization An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-02T15:37:06.696533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b8b87a55-27e6-4d8d-ac66-9101f3908aad · inbound

An Exploratory Case Study of LLM-Assisted Refactoring and Gameplay Feature Generation in an Endless Runner Game cites this paper.

An Exploratory Case Study of LLM-Assisted Refactoring and Gameplay Feature Generation in an Endless Runner Game An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-26T13:59:30.549631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bfccf4a8-30c1-40e2-8b85-05fe788cda32 · inbound

CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues cites this paper.

CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:20:07.004777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f02582d4-7f5f-4e05-8fea-38fab94d0134 · inbound

CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues cites this paper.

CodeChat-Eval: Evaluating Large Language Models in Multi-Turn Code Refinement Dialogues An Empirical Study on the Potential of LLMs in Automated Software Refactoring

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:55:35.356545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.