Trust-Calibrated Code Review: A Participatory Design Study of Review Workflows for LLM-Generated Multi-File Changes
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
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2026
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| _version_ | 1866918534996557824 |
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| author | Heander, Lo Gullstrand Sergeyuk, Agnia Zakharov, Ilya Söderberg, Emma Mukhortov, Nikita |
| author_facet | Heander, Lo Gullstrand Sergeyuk, Agnia Zakharov, Ilya Söderberg, Emma Mukhortov, Nikita |
| contents | Background: Developers increasingly review multi-file code changes generated by LLM-based agents, yet no validated end-to-end workflow or IDE tooling design exists for this scenario.
Aims: We investigate (RQ1) the challenges developers face when reviewing LLM-generated multi-file changes and (RQ2) how developers envision effective workflows for this task.
Method: In collaboration with JetBrains, we conducted a participatory design study structured using the double-diamond design process with Discover, Define, Develop, and Deliver phases. Industry practitioners participated in the Discover phase (N=17); seven of these returned for the Develop phase. The Define phase was an author-led synthesis. The Deliver phase produced a conceptual design and a high-fidelity semi-interactive prototype evaluated through a follow-up survey with N=43 practitioners.
Results: Participants identified trust-calibration as the central challenge. The study yielded a three-level review workflow (overview, file-analysis, code snippet review) supported by seven design constructs (chunk, risk-per-line, risk-per-file, judge, walk-through, zooming in/out, and security cage). In the validation survey, all three workflow levels scored above the neutral midpoint (means 3.50--3.91 on a five-point scale). Of the respondents, 63% expected reduced overall review effort, and 52% reduced trust-assessment effort, relative to their current tools. These findings suggest that the design constructs indicate a positive direction for future tool development.
Conclusions: Reviewing LLM-generated multi-file changes is a trust-calibration problem rather than a diffing problem. The three-level workflow and the seven constructs we report give tool designers a conceptual framework for building AI-ready code review tools that surface risk and confidence signals at the granularity at which developers allocate attention. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2606_01969 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Trust-Calibrated Code Review: A Participatory Design Study of Review Workflows for LLM-Generated Multi-File Changes Heander, Lo Gullstrand Sergeyuk, Agnia Zakharov, Ilya Söderberg, Emma Mukhortov, Nikita Software Engineering Human-Computer Interaction H.5.2; D.2.9; D.2.6 Background: Developers increasingly review multi-file code changes generated by LLM-based agents, yet no validated end-to-end workflow or IDE tooling design exists for this scenario. Aims: We investigate (RQ1) the challenges developers face when reviewing LLM-generated multi-file changes and (RQ2) how developers envision effective workflows for this task. Method: In collaboration with JetBrains, we conducted a participatory design study structured using the double-diamond design process with Discover, Define, Develop, and Deliver phases. Industry practitioners participated in the Discover phase (N=17); seven of these returned for the Develop phase. The Define phase was an author-led synthesis. The Deliver phase produced a conceptual design and a high-fidelity semi-interactive prototype evaluated through a follow-up survey with N=43 practitioners. Results: Participants identified trust-calibration as the central challenge. The study yielded a three-level review workflow (overview, file-analysis, code snippet review) supported by seven design constructs (chunk, risk-per-line, risk-per-file, judge, walk-through, zooming in/out, and security cage). In the validation survey, all three workflow levels scored above the neutral midpoint (means 3.50--3.91 on a five-point scale). Of the respondents, 63% expected reduced overall review effort, and 52% reduced trust-assessment effort, relative to their current tools. These findings suggest that the design constructs indicate a positive direction for future tool development. Conclusions: Reviewing LLM-generated multi-file changes is a trust-calibration problem rather than a diffing problem. The three-level workflow and the seven constructs we report give tool designers a conceptual framework for building AI-ready code review tools that surface risk and confidence signals at the granularity at which developers allocate attention. |
| title | Trust-Calibrated Code Review: A Participatory Design Study of Review Workflows for LLM-Generated Multi-File Changes |
| topic | Software Engineering Human-Computer Interaction H.5.2; D.2.9; D.2.6 |
| url | https://arxiv.org/abs/2606.01969 |