English

AuditCoder: Responsibility-Preserving Task Graphs for Auditable Code Generation and Bounded Repair

Software Engineering 2026-07-31 v1

Abstract

Code generators return programs, but typically do not preserve the construction record needed to connect a failure to the decision that produced the affected code or to delimit a justified repair. We present AuditCoder, which treats the program and an auditable construction trace as joint outputs. Before code generation, a contract-annotated task graph assigns stable responsibility identities that remain attached to each commitment, its owned implementation, provenance, validation evidence, and intervention history. When validation fails, a conservative locator maps heterogeneous evidence to a node or dependency branch---or abstains---and bounded repair regenerates only that region while reusing the frozen complement. On APPS, \method{} reaches 82.582.5--83.0%83.0\% \texttt{pass@1}, recovering much of the loss caused by unrepaired graph decomposition but trailing AgentCoder by 7.57.5--8.58.5 points. On ClassEval, it reaches 75.075.0--82.0%82.0\%, outperforming CoT + retry while remaining below AgentCoder. A separate audit of 200 APPS records yields 0.97250.9725 task-macro decision--code trace coverage; the locator identifies an evidence-supported node or branch for 26 of 60 failures, and 17 of those localized repairs pass. For tasks with stable, locally testable boundaries, the graph functions not only as a decomposition structure but also as a persistent index for validation and repair.

Cite

@article{arxiv.2607.29529,
  title  = {AuditCoder: Responsibility-Preserving Task Graphs for Auditable Code Generation and Bounded Repair},
  author = {Kangjie Huang and Chen Lyu},
  journal= {arXiv preprint arXiv:2607.29529},
  year   = {2026}
}

Comments

Preprint. 37 pages, 5 figures. Code and data are available at the project repository