Vibe coding: code-review and debugging comparison framework

Evidence & verification

Source level

Peer-reviewed source
Grounded in a peer-reviewed publication. This describes the source; it does not mean the reported results have been independently reproduced.

Outcome verification

Not empirically evaluated here
A documented resource or intended workflow, not a demonstrated academic outcome. No empirical benefit is established by its inclusion.

Sources checked

2026-10-19 (UTC)

Source scope: Primary abstract and selected publisher PDF methods/limitations, with stated journal policy. Documentation/reference inclusion does not establish an empirical research benefit. The journal-source label follows publication identity and available journal metadata/policy, not an audit of review conduct or scientific quality.

Source-checked does not mean independently reproduced. See the Method page for how these labels are assigned.

Sources (2)

Research applicability

A proposed comparison design for AI-assisted code generation, review and debugging research.

Getting started

Read the linked primary sources and the stated adoption requirements. Reuse suggestions are editorial and untested; no setup recipe or trial was executed.

Maintenance

Sources last checked on 2026-10-19. Future availability, maintenance, provider terms and compatibility were not verified.

License

The publisher claims CC BY-SA 4.0; article-specific rights and current terms were not independently audited.

Workflow & human oversight

No workflow level assigned. Selected PDF methods propose a secondary-data evaluation reference: generation speed, integrity and cognitive layers; source/cohort comparability and metric standardisation; prompt-to-code mapping, logic audit and time accounting. A complete AI-assisted research workflow and final human acceptance are not established.

Workflow level is not an evidence score; higher is not better evidence.

Approach

The proposed framework organises secondary data into generation-speed, integrity and cognitive layers. It calls for comparable sources/cohorts and standardised metrics, then maps prompts to code, audits logic and compares generation/review/debugging time against traditional baselines. These are documented instructions, not an executed study or verified causal effects.

Limitations

Primary abstract, selected publisher PDF methods/limitations/reference context and stated journal policy only; not a full critical audit of data, code or tools. The abstract’s 50-developer wording differs from the body’s secondary-data/meta-analytical virtual experiment and minimum/aggregate cohort rules; no new 50-participant experiment is claimed. The parsed PDF may be cached; raw/version parity is unverified. Prestige/source filters do not prove quality, and operational metrics and included-data traceability remain unclear. Strong time, bug-rate, causal, psychological and pedagogical effects were not validated. Tangential references do not establish misconduct. The source label is not an audit of review conduct, indexing or impact factor.

Reproducibility

Source text was checked only within this scope: Primary abstract and selected publisher PDF methods/limitations, with stated journal policy. No software, dataset, experiment or result was independently reproduced.

Adoption requirements

Untested suggestion: inspect protocol, task complexity, metrics, cohort selection and baseline comparability before designing an evaluation.

Comments

No comments yet.

Add a comment

Comments are held for moderation before appearing. Critical or corrective comments are welcome — especially evidence that an entry overstates what has been verified.