MemHint combines LLM classification of custom memory functions with Z3 path validation to augment CodeQL and Infer, detecting 52 memory leaks (49 confirmed) across 3.4M LOC versus 19 and 3 by vanilla tools.
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6 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.SE 6years
2026 6representative citing papers
XSearch achieves explainable code search by breaking queries into functional concepts and matching them directly to code statements, delivering large gains on out-of-distribution benchmarks.
A review of 114 studies creates taxonomies for code and data quality issues, formalizes 18 propagation mechanisms from training data defects to LLM-generated code defects, and synthesizes detection and mitigation techniques.
GALA uses hierarchical graph alignment between UI screenshots and code structures to achieve state-of-the-art bug localization in multimodal automated program repair on SWE-bench.
More fault localization context does not consistently improve LLM-based program repair; file-level context gives 15-17x gains, optimal around 6-10 files, while line-level context often degrades performance from noise.
V2E automates PoC generation, triggerability and profitability validation, and iterative refinement using LLMs to confirm exploitable smart contract vulnerabilities, outperforming baselines on 264 labeled contracts.
citing papers explorer
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Finding Memory Leaks in C/C++ Programs via Neuro-Symbolic Augmented Static Analysis
MemHint combines LLM classification of custom memory functions with Z3 path validation to augment CodeQL and Infer, detecting 52 memory leaks (49 confirmed) across 3.4M LOC versus 19 and 3 by vanilla tools.
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XSearch: Explainable Code Search via Concept-to-Code Alignment
XSearch achieves explainable code search by breaking queries into functional concepts and matching them directly to code statements, delivering large gains on out-of-distribution benchmarks.
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Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code
A review of 114 studies creates taxonomies for code and data quality issues, formalizes 18 propagation mechanisms from training data defects to LLM-generated code defects, and synthesizes detection and mitigation techniques.
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GALA: Multimodal Graph Alignment for Bug Localization in Automated Program Repair
GALA uses hierarchical graph alignment between UI screenshots and code structures to achieve state-of-the-art bug localization in multimodal automated program repair on SWE-bench.
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On the Role of Fault Localization Context for LLM-Based Program Repair
More fault localization context does not consistently improve LLM-based program repair; file-level context gives 15-17x gains, optimal around 6-10 files, while line-level context often degrades performance from noise.
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V2E: Validating Smart Contract Vulnerabilities through Profit-driven Exploit Generation and Execution
V2E automates PoC generation, triggerability and profitability validation, and iterative refinement using LLMs to confirm exploitable smart contract vulnerabilities, outperforming baselines on 264 labeled contracts.