This paper proposes a portable inlining-prediction framework for lightweight systems, using production compiler diagnostics, an extractor, and a trained predictor.

AutoPass is a multi-agent framework for compiler performance tuning using a large language model, enabling it to query compiler-internal optimization states and analyze the intermediate representation…

KoAT is a tool that automatically infers complexity bounds and proves termination of integer programs using an alternating modular analysis approach and a portfolio of techniques.

This paper introduces a novel class of backdoor attacks that exploit the numerical side effects of LLM inference optimization, achieving high success rates while maintaining clean accuracy.

KLineage introduces a novel method to teach LLMs when and how to apply GPU kernel optimizations by reverse-engineering expert kernel lineages, resulting in superior optimization skills compared to exi…

Elevator is a novel, deterministic binary translator that statically translates entire x86-64 executables to AArch64 by considering all possible interpretations of every byte, eliminating the need for…

AI-PROPELLER introduces a novel interprocedural code layout optimization system that uses an agentic evolutionary workflow to achieve significant, measurable performance gains in large-scale, real-wor…

This paper proposes an automated static verification method for a subset of WebAssembly using a CHCs satisfiability solver, addressing challenges of handling indirect function calls and analyzing larg…

The paper proposes a general, compiler-integrated framework for secure content composition that minimizes the syntactic difference between secure and insecure coding practices.

The paper proposes a new binary format that embeds compiler-generated metadata into executables, making the binary structure more transparent and enabling reliable analysis, instrumentation, and recom…

The paper introduces Spaghetti Architect, a tool that generates controlled code datasets for machine learning models by deliberately adding redundancy, messiness, and difficulty.

The paper proposes TRAVEL, a framework for automated C-to-Rust translation using Monte Carlo Tree Search and reinforcement learning, improving accuracy and success rate.

Kani is an open-source model checker for Rust that provides correctness guarantees for safety properties through compilation and a specification language.

This paper proposes a method for verifying functional correctness of message-passing concurrent programs using Constrained Horn Clause (CHC) solving.

The paper proposes integrating dependent pattern matching into the unification process in dependently typed languages to synthesize functions defined by case analysis, addressing the limitation of exi…

The paper introduces CodeGolf Bench, a novel multi-language benchmark using code golf to measure LLMs' ability to generate highly concise and efficient code, showing that reasoning models significantl…