A cascaded large-small model system generates edit sketches with the large model and applies them with the small model to make code editing both accurate and token-efficient.
Large language models (LLMs) for source code analysis: applications, models and datasets
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PrismaDV generates task-aware data unit tests by jointly analyzing downstream code and dataset profiles, outperforming task-agnostic baselines on new benchmarks spanning 60 tasks, with SIFTA enabling automatic prompt optimization that beats hand-written prompts.
ORBIT achieves 100% compilation success and 91.7% test success on 24 mostly large programs from CRUST-Bench by using dependency-aware orchestration and iterative verification, outperforming prior static and baseline tools.
LLM4CodeRE adapts LLMs with multi-adapter and seq2seq fine-tuning for accurate assembly-to-source decompilation and reverse translation in code reverse engineering.
SafeTrans achieves up to 80% successful C-to-Rust translations via LLM iterative repair on 2653 programs and two real projects, with some C vulnerabilities carrying over to the Rust output.
Survey mapping LLM applications in software quality assurance to established standards including ISO/IEC 12207, ISO 25010, CMMI, and TMM, with case studies, challenges, and future directions.
citing papers explorer
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Cascaded Code Editing: Large-Small Model Collaboration for Effective and Efficient Code Editing
A cascaded large-small model system generates edit sketches with the large model and applies them with the small model to make code editing both accurate and token-efficient.
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PrismaDV: Automated Task-Aware Data Unit Test Generation
PrismaDV generates task-aware data unit tests by jointly analyzing downstream code and dataset profiles, outperforming task-agnostic baselines on new benchmarks spanning 60 tasks, with SIFTA enabling automatic prompt optimization that beats hand-written prompts.
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ORBIT: Guided Agentic Orchestration for Autonomous C-to-Rust Transpilation
ORBIT achieves 100% compilation success and 91.7% test success on 24 mostly large programs from CRUST-Bench by using dependency-aware orchestration and iterative verification, outperforming prior static and baseline tools.
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LLM4CodeRE: Generative AI for Code Decompilation Analysis and Reverse Engineering
LLM4CodeRE adapts LLMs with multi-adapter and seq2seq fine-tuning for accurate assembly-to-source decompilation and reverse translation in code reverse engineering.
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SafeTrans: LLM-assisted Transpilation from C to Rust
SafeTrans achieves up to 80% successful C-to-Rust translations via LLM iterative repair on 2653 programs and two real projects, with some C vulnerabilities carrying over to the Rust output.
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A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards
Survey mapping LLM applications in software quality assurance to established standards including ISO/IEC 12207, ISO 25010, CMMI, and TMM, with case studies, challenges, and future directions.