26,098 papers · page 77 of 1,305
Large Language Models (LLMs) have rapidly gained popularity, transforming research and industry. To support their adoption, LLM agent workflow orchestration frameworks (hereinafter referred to as LLM agent frameworks) like LangChain have become essential for building advanced app…
Ensuring the safety and reliability of Cyber-Physical Systems (CPS) is critical, particularly in safety-critical domains such as automotive and aerospace. Fault Injection (FI) is a well-established technique for testing system resilience, but current FI tools often face challenge…
As invisible image watermarking gains importance for verifying AI-generated content, consistency and reproducibility remain major challenges due to the diverse methods, datasets, attacks, and metrics.We aim to provide a flexible, extensible, and user-friendly framework that enabl…
As software development increasingly relies on external collaboration, organizations face new risks of intellectual property leakage beyond traditional concerns about deployed software. Even when the source code is protected, adversaries may infer sensitive internal program speci…
Guardrails are critical for the safe deployment of Large Language Models (LLMs)-powered software. Unlike traditional rule-based systems with limited, predefined input-output spaces that inherently constrain unsafe behavior, LLMs enable open-ended, intelligent interactions—opening…
The distributed deep learning training process within large-scale clusters serves as the foundation of contemporary artificial intelligence. However, its inherent characteristics make it particularly sensitive to stragglers, specifically the presence of slow workers, which can si…
Rust is a programming language that combines memory safety and low-level control, providing C-like performance while guaranteeing the absence of undefined behaviors by default. Rust’s growing popularity has prompted research on correct and idiomatic transpiling of existing code-b…
Type errors in Python often lead to runtime failures, posing significant challenges to software reliability and developer productivity. Existing static analysis tools aim to detect such errors without execution but frequently suffer from high false positive rates. Recently, unit …
Among the programming languages for Programmable Logic Controllers (PLCs), Structured Text (ST) is widely adopted for industrial automation due to its expressiveness and flexibility. However, major vendors implement ST with proprietary extensions and hardware-specific libraries -…
Current call graph generation methods for ArkTS, a new programming language for OpenHarmony, exhibit precision limitations when supporting advanced static analysis tasks such as data flow analysis and vulnerability pattern detection, while the workflow of traditional JavaScript(J…
Recent advances in large language models (LLMs) have enabled promising performance in unit test generation through in-context learning (ICL). However, the quality of in-context examples significantly influences the effectiveness of generated tests—poorly structured or semanticall…
Trustworthy evaluation methods for code snippets play a crucial role in neural code generation. Traditional methods, which either rely on reference solutions or require executable test cases, have inherent limitation in flexibility and scalability. The recent LLM-as-Judge methodo…
An open source Linux distribution often undergoes version upgrades and migrations, which is prone to incompatibility issues especially when it comes to large-scale software changes. Although differential testing has been widely used in software testing, it is still challenging to…
Reproducing game bugs, particularly crash bugs in continuously evolving games like Minecraft, is a notoriously manual, time-consuming, and challenging process to automate; insights from a key decision maker from Minecraft we interviewed confirm this, highlighting that a substanti…
The rise of blockchain has brought smart contracts into mainstream use, creating a demand for smart contract generation tools. While large language models (LLMs) excel at generating code in general-purpose languages, their effectiveness on Solidity, the primary language for smart…
As quantum computing continues to emerge, ensuring the quality of quantum programs has become increasingly critical. Quantum program testing has emerged as a prominent research area within the scope of quantum software engineering. While numerous approaches have been proposed to …
Static code analysis cannot detect real-time interaction issues faced by users with disabilities. We propose a multi-modal Artificial Intelligence (AI) agent framework that simulates interactions of users with visual impairments without code access. The agent would closely simula…
In the field of human-computer interaction (HCI), alternative interaction methods are becoming increasingly popular and commercially available. From this opportunity came EyeNav, a system that combines eye-tracking and natural language processing (NLP) to enhance accessibility an…
Recently, Large Language Models (LLMs) have gained attention for their ability to handle a broad range of tasks, including unit test generation. Despite their success, LLMs may exhibit hallucinations when generating unit tests for focal methods or functions due to their lack of a…
WebAssembly (Wasm) is a low-level binary instruction format designed for safe and high-performance execution across diverse computing environments and runtimes. As Wasm evolves with new features and proposals, testing the correctness and conformance of Wasm runtimes has become in…