3,458 papers · page 18 of 173
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…
Evaluating the code generation capabilities of Large Language Models (LLMs) remains an open question. Recently, more advanced benchmarks—such as CoderEval, EvoCodeBench, and ClassEval—have been introduced to evaluate LLMs on practical coding tasks from GitHub repositories, such a…
As cloud service systems grow in scale and complexity, incidents that indicate unplanned interruptions and outages become unavoidable. Rapid and accurate triage of these incidents to the appropriate responsible teams is crucial to maintain service reliability and prevent signific…
Alerts are critical for detecting anomalies in large-scale cloud systems, ensuring reliability and user experience. However, current systems generate overwhelming volumes of alerts, degrading operational efficiency due to ineffective alert life-cycle management. This paper detail…
As Code Language Models (CLMs) are increasingly used to automate multilingual code intelligence tasks, Full-Parameter Fine-Tuning (FPFT) of CLMs has become a widely adopted approach, which is both time-consuming and resource-intensive. Parameter-Efficient Fine-Tuning (PEFT) provi…
Symbol recovery in reverse engineering is crucial for restoring variable and data structure information in compiled binaries. While learning-based methods have shown promise in recovering both semantic information (names and types) and syntactic information (shapes), they require…
Smart contracts are a core component of blockchain ecosystems, but their transparency and immutability make them vulnerable to attacks, leading to significant financial losses. Thus, repairing vulnerabilities in smart contracts is crucial for establishing a trustworthy blockchain…
When fuzzing a proprietary file-processing program, one typically executes the whole program repeatedly with sampled input files, and distinguishes between normal and abnormal termination. While this works well for many command-line utilities, it is more complicated for programs …
The abstract syntax tree differencing (ASTDiff) technique aims to capture syntactic code changes through comparing the differences between a pair of ASTs of a program, which has been widely used in various program analysis or testing tasks, such as code review, clone detection, a…
Deep learning programs are continually enhanced for improved performance through the use of kernel-level optimizations, parallel training, and low-precision arithmetic. These optimizations provide different implementations that are mathematically equivalent. Round-off error in fl…
The Linux kernel network stack is a critical component of modern operating systems, widely deployed across platforms and often exposed to untrusted inputs. Its complex and stateful nature makes it a frequent target of security vulnerabilities, particularly those triggered by subt…
Reading code is a fundamental activity in both software engineering and computer science education. Understanding the cognitive processes involved in reading code is crucial for identifying effective cognitive strategies, which can inform teaching methods and tooling support for …