aogavrilov/inspectable-control-results

Inspectable Control for Structure-Preserving Software Regeneration — reported result summary

This repository contains an author-maintained, machine-readable summary of the key quantitative values reported in Inspectable Control for Structure-Preserving Software Regeneration.

Scope: this is a small table-level result summary. It is not the underlying training corpus, evaluation corpus, model code, checkpoint, benchmark release, or a new experimental run.

Publication

• Canonical publication page: https://aogavrilov.com/publications/inspectable-control/
• DOI: https://doi.org/10.1145/3803437.3807386
• Authors: Alexey Gavrilov, Alan-Barsag Gazzaev, Mikhail Mozikov, Ilya Makarov, Sergey Muravyov
• Venue: Proceedings of the 34th ACM International Conference on the Foundations of Software Engineering
• Open result section: https://aogavrilov.com/publications/inspectable-control/#results
• Hugging Face collection: https://huggingface.co/collections/aogavrilov/publication-result-summaries-6a6b733b3116a87befb37ec2

Reader guides

• English paper guide: https://aogavrilov.com/publications/inspectable-control/
• Руководство на русском: https://aogavrilov.com/ru/publications/inspectable-control/
• 简体中文论文导读: https://aogavrilov.com/zh/publications/inspectable-control/
• Problem-first guide — How can AI edit code without regenerating the entire program?: English · Русский · 简体中文

Files

• results.csv — table shown in the Dataset Viewer.
• results.json — table plus DOI, metric, sample-size, condition, uncertainty, and takeaway metadata.
• results.md — human-readable result summary.
• citation.bib — BibTeX record for the paper.
• manifest.json and SHA256SUMS — source links and integrity metadata for this export.

Experimental scope recorded by the paper

• Source data: A preprocessed subset of CodeParrot Clean containing 2,000 Python functions.
• Reported sample size: 2,000 preprocessed Python functions; conditional sample uniqueness is 0.998.
• Conditions: 64-token functions, argmax decoding, 16 top-level codes and 32 lower-level codes; full locking exactly recovers the codec reconstruction.
• Metrics: Parse rate; Skeleton and signature preservation proxies; Unlocked-position change rate; Sample uniqueness and entropy
• Main reported takeaway: Coarse latent locking improves syntactic stability without collapsing change in the editable region; the result demonstrates structural control, not guaranteed functional equivalence.

Limitations

• Statistical uncertainty: The two-page study reports point estimates without confidence intervals or multi-seed statistical analysis.
• Data boundary: The sample is not representative of repository-scale software, multiple programming languages, or behaviorally verified repair tasks.
• Version boundary: A dataset checksum and immutable snapshot identifier are not reported in the two-page paper.
• Reproducibility boundary: A public installation recipe is not yet available; no inactive Code button is shown.

Do not treat absent values as zero, infer functional correctness from structural proxies, or transfer the reported ranking beyond the stated experimental setting.

Rights and provenance

The author manuscript and this result-summary export are identified as CC BY 4.0. The upstream data described by the paper retain their own terms.

No dataset files are redistributed by this site; reuse remains subject to the upstream CodeParrot dataset and source-code licenses.

The authoritative context and current rights statement are maintained at https://aogavrilov.com/publications/inspectable-control/#data.

Citation

@inproceedings{Gavrilov2026InspectableControl,
  title      = {Inspectable Control for Structure-Preserving Software Regeneration},
  author     = {Gavrilov, Alexey and Gazzaev, Alan-Barsag and Mozikov, Mikhail and Makarov, Ilya and Muravyov, Sergey},
  booktitle  = {Proceedings of the 34th ACM International Conference on the Foundations of Software Engineering},
  publisher  = {ACM},
  year       = {2026},
  pages      = {1406--1407},
  doi        = {10.1145/3803437.3807386},
  url        = {https://doi.org/10.1145/3803437.3807386},
  isbn       = {979-8-4007-2636-1},
}