Mitigating Implicit Inconsistencies in Patch Porting
This addresses the challenge of reducing manual effort and delays in patch porting for software developers, particularly in cross-fork and cross-branch scenarios, though it is incremental by building on prior automated approaches.
The paper tackled the problem of implicit inconsistencies in automated patch porting between codebases, which existing methods struggle with due to non-local mapping requirements, and resulted in MIP resolving over twice as many patches as the best baseline in experiments.
Promptly porting patches from a source codebase to its variants (e.g., forks and branches) is essential for mitigating propagated defects and vulnerabilities. Recent studies have explored automated patch porting to reduce manual effort and delay, but existing approaches mainly handle inconsistencies visible in a patch's local context and struggle with those requiring global mapping knowledge between codebases. We refer to such non-local inconsistencies as implicit inconsistencies. Implicit inconsistencies pose greater challenges for developers to resolve due to their non-local nature. To address them, we propose MIP, which enables collaboration among an LLM, a compiler, and code analysis utilities. MIP adopts different strategies for different cases: when source identifiers exist in the target codebase, it leverages compiler diagnostics; otherwise, it retrieves matched code segment pairs from the two codebases as mapping knowledge for mitigation. Experiments on two representative scenarios, cross-fork and cross-branch patch porting, show that MIP successfully resolves more than twice as many patches as the best-performing baseline in both settings. A user study with our industry partner further demonstrates its practical effectiveness.