4,951 papers · page 9 of 248
Deep Learning (DL) compilers typically load a DL model and optimize it with intermediate representation. Existing DL compiler testing techniques mainly focus on model optimization stages, but rarely explore bug detection at the model loading stage. Effectively testing the model l…
Library APIs are used by virtually every modern application and system, making them among today's most security-critical software. In recent years, library bug-finding efforts have overwhelmingly adopted the powerful testing strategy of coverage-guided fuzzing. At its core, API f…
Large language models have catalyzed an unprece-dented wave in code generation. While achieving significant advances, they blur the distinctions between machine- and human-authored source code, causing integrity and authenticity issues of software artifacts. Previous methods such…
The shift-left principle in the industry requires us to test a software application as early as possible. In particular, when code changes in a microservice application are committed to the code repository, we have to efficiently identify all public microservice interfaces affect…
Micro frontend (MFE) architectures have gained significant popularity for promoting independence and modularity in development. Despite their widespread adoption, the field remains relatively unexplored, especially concerning identifying problems and documenting best practices. D…
The Open Network (TON), designed to support Telegram's extensive user base of hundreds of millions, has garnered considerable attention since its launch in 2022. FunC is the most popular programming language for writing smart contracts on TON. It is distinguished by a unique synt…
The ability to execute code is a prerequisite for various dynamic program analyses. Learning-guided execution has been proposed as an approach to enable the execution of arbitrary code snippets by letting a neural model predict likely values for any missing variables. Although st…
Machine learning models are widely used, but can also often be wrong. Users would benefit from a reliable indication of whether a given output from a given model should be trusted, so a rational decision can be made whether to use the output or not. For example, outputs can be as…
Security vulnerabilities impose significant costs on users and organizations. Detecting and addressing these vulnerabilities early is crucial to avoid exploits and reduce development costs. Recent studies have shown that deep learning models can effectively detect security vulner…
Artificial Intelligence (AI) techniques, especially Large Language Models (LLMs), have started gaining popularity among researchers and software developers for generating source code. However, LLMs have been shown to generate code with quality issues and also incurred copyright/l…
Neural code models (NCMs) have demonstrated extraordinary capabilities in code intelligence tasks. Meanwhile, the security of NCMs and NCMs-based systems has garnered increasing attention. In particular, NCMs are often trained on large-scale data from potentially untrustworthy so…
Code-line-Ievel defect prediction (CLDP) is an effective technique to incorporate comprehensive measures for buggy line identification to optimize efforts in Software Quality Assurance activities. Most CLDP methods either consider the textual information of the code or rely merel…
To support software developers in understanding and maintaining programs, various automatic (source) code summarization techniques have been proposed to generate a concise natural language summary (i.e., comment) for a given code snippet. Recently, the emergence of large language…
Autonomous Vehicles (AVs) are advancing rapidly, with Level-4 AVs already operating in real-world conditions. Current AVs, however, still lag behind human drivers in adaptability and performance, often exhibiting overly conservative behaviours and occasionally violating traffic l…
Decentralized Finance (DeFi) is an emerging paradigm within the blockchain space that aims to revolutionize conventional financial systems by applying blockchain technology. The substantial value of digital assets managed by DeFi protocols makes it a lucrative target for attacks.…
Hallucinations, the tendency to produce irrelevant/incorrect responses, are prevalent concerns in generative AIbased tools like ChatGPT. Although hallucinations in ChatGPT are studied for textual responses, it is unknown how ChatGPT hallucinates for technical texts that contain b…
Identifying recurring vulnerabilities is crucial for ensuring software security. Clone-based techniques, while widely used, often generate many false alarms due to the existence of similar but patched (SBP) code, which is similar to vulnerable code but is not vulnerable due to ha…
Reinforcement Learning (RL) is increasingly adopted to train agents that can deal with complex sequential tasks, such as driving an autonomous vehicle or controlling a humanoid robot. Correspondingly, novel approaches are needed to ensure that RL agents have been tested adequatel…
Formal verification using proof assistants, such as Coq, enables the creation of high-quality software. However, the verification process requires significant expertise and manual effort to write proofs. Recent work has explored automating proof synthesis using machine learning a…
Code generation is to automatically generate source code conforming to a given programming specification, which has received extensive attention especially with the development of large language models (LLMs). Due to the inherent difficulty of code generation, the code generated …