AOCI creates an incremental symbolic-semantic index per code unit that gives LLMs a complete, consistent repository view, outperforming baselines with zero defects on 19 industrial tasks while using far fewer tokens.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.SE 2years
2026 2representative citing papers
AI IDEs with structured guidance can produce functional large-scale code but frequently introduce design flaws such as duplication, complexity, and principle violations that risk long-term maintainability.
citing papers explorer
-
AOCI: Symbolic-Semantic Indexing for Practical Repository-Scale Code Understanding with LLMs
AOCI creates an incremental symbolic-semantic index per code unit that gives LLMs a complete, consistent repository view, outperforming baselines with zero defects on 19 industrial tasks while using far fewer tokens.
-
Beyond Functional Correctness: Design Issues in AI IDE-Generated Large-Scale Projects
AI IDEs with structured guidance can produce functional large-scale code but frequently introduce design flaws such as duplication, complexity, and principle violations that risk long-term maintainability.