AuditCoder: Responsibility-Preserving Task Graphs for Auditable Code Generation and Bounded Repair
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 -- \texttt{pass@1}, recovering much of the loss caused by unrepaired graph decomposition but trailing AgentCoder by -- points. On ClassEval, it reaches --, outperforming CoT + retry while remaining below AgentCoder. A separate audit of 200 APPS records yields 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