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 Athena, a novel impact analysis approach that combines dependence graph information with conceptual coupling using deep representation learning.

The paper introduces a novel memory forensics framework to perform runtime analysis of Go malware, successfully recovering critical execution state and artifacts that are invisible to traditional stat…

The paper introduces the first byte-native Large Language Model (LLM) capable of analyzing raw executable binary data, achieving high accuracy in tasks like malware and architecture classification.

The paper introduces SymTEE, an LLM-assisted symbolic execution framework that detects missing input validation vulnerabilities in TEE applications without needing complex, real TEE setups.

The paper introduces Clover, a code completion tool that logs students' interactions and offers attention checks to promote reflective engagement during programming tasks.

MemHint is a neuro-symbolic static analysis pipeline that significantly improves memory leak detection in C/C++ by combining LLM semantic understanding with Z3 symbolic reasoning, detecting more leaks…

This survey analyzed 132 web application security tutorials, finding that most lack concrete implementation details and recommending that the presence of runnable code and links to official resources…

The paper presents Symbolon, a framework that learns and applies context-sensitively diverse code transformations to improve symbolic execution, increasing coverage and reducing costs.

This paper evaluates the improvement of statistical fault localization by augmenting it with execution features.

This paper systematically surveys adaptive and AI-augmented security testing, concluding that a major gap exists—structural-adaptive fragmentation—where current systems fail to integrate structural pr…

The paper introduces Code-QA-Bench, a novel framework that rigorously separates genuine code reasoning from mere documentation memorization in repository-level code understanding benchmarks.

This paper analyzes various source-to-bytecode obfuscation techniques for Erlang, demonstrating that effective protection relies on exploiting the representational gaps between high-level semantics an…

This paper proposes using transformer-based models on program slices to accurately detect C/C++ software vulnerabilities by capturing both local and global contextual information.

The paper proposes a generic memory framework for advanced static program analysis, supporting various memory behaviors from different programming languages using Abstract Interpretation theory.

This paper explores using Knowledge Components (KCs) as interpretable signals to understand assignment difficulty and student struggle in intro programming courses.

This paper evaluates Centaur, a foundation model trained on psychological experiments, for program comprehension tasks and compares its performance to Llama 3.1.

SEMBridge is a tagless-final framework that allows a single executable object program to generate multiple program semantics, including weakest-precondition and bounded-checking interpretations, ensur…

The paper introduces Symbolicate-Enrich-Sample, a pipeline that efficiently filters millions of functions in a Windows OS to create a highly prioritized, manageable shortlist of potential vulnerabilit…

The paper introduces Symbolicate-Enrich-Sample, a low-cost pipeline that drastically reduces the search space of a whole operating system by prioritizing vulnerable functions, turning millions of pote…