相关论文: Automating SBOM Generation with Zero-Shot Semantic…
Modern software engineering increasingly relies on open, community-driven standards, yet how such standards are created in fast-evolving domains like AI-powered systems remains underexplored. This paper presents a detailed experience report…
Binary similarity detection is a critical technique that has been applied in many real-world scenarios where source code is not available, e.g., bug search, malware analysis, and code plagiarism detection. Existing works are ineffective in…
The recent segmentation foundation model, Segment Anything Model (SAM), exhibits strong zero-shot segmentation capabilities, but it falls short in generating fine-grained precise masks. To address this limitation, we propose a novel…
Verifying that a compiled binary originates from its claimed source code is a fundamental security requirement, called source code provenance. Achieving verifiable source code provenance in practice remains challenging. The most popular…
When reverse engineering a binary, the analyst must first understand the semantics of the binary's functions through either manual or automatic analysis. Manual semantic analysis is time-consuming, because abstractions provided by high…
Software Bills of Materials (SBOMs) have become a regulatory requirement for improving software supply chain security and trust by means of transparency regarding components that make up software artifacts. However, enterprise and regulated…
Checking the semantic equivalence of operations is an important task in software development. For instance, regression testing is a routine task performed when software systems are developed and improved, and software package managers…
Source code summarization involves creating brief descriptions of source code in natural language. These descriptions are a key component of software documentation such as JavaDocs. Automatic code summarization is a prized target of…
Modern digital ecosystems, spanning software, hardware, learning models, datasets, and cryptographic products, continue to grow in complexity, making it difficult for organizations to understand and manage component dependencies. Bills of…
When it comes to deploying deep vision models, the behavior of these systems must be explicable to ensure confidence in their reliability and fairness. A common approach to evaluate deep learning models is to build a labeled test set with…
A number of high-level languages and libraries have been proposed that offer novel and simple to use abstractions for concurrent, asynchronous, and distributed programming. The execution models that realise them, however, often change over…
Reducing the cost of sequencing genomes provided by next-generation sequencing technologies has greatly increased the number of genomic projects. As a result, there is a growing need for better assembly and assembly validation methods. One…
Security of software supply chains is necessary to ensure that software updates do not contain maliciously injected code or introduce vulnerabilities that may compromise the integrity of critical infrastructure. Verifying the integrity of…
Zero-shot sketch-based image retrieval (SBIR) is an emerging task in computer vision, allowing to retrieve natural images relevant to sketch queries that might not been seen in the training phase. Existing works either require aligned…
Throughout computer history, it has been repeatedly demonstrated that critical software vulnerabilities can significantly affect the components involved. In the Free/Libre and Open Source Software (FLOSS) ecosystem, most software is…
Software debloating seeks to mitigate security risks and improve performance by eliminating unnecessary code. In recent years, a plethora of debloating tools have been developed, creating a dense and varied landscape. Several studies have…
Semantic segmentation is a significant perception task in autonomous driving. It suffers from the risks of adversarial examples. In the past few years, deep learning has gradually transitioned from convolutional neural network (CNN) models…
Zero-shot object counting (ZOC) aims to enumerate objects in images using only the names of object classes during testing, without the need for manual annotations. However, a critical challenge in current ZOC methods lies in their inability…
Neural networks have become integral to many fields due to their exceptional performance. The open-source community has witnessed a rapid influx of neural network (NN) repositories with fast-paced iterations, making it crucial for…
Software testing is an important and essential part of the software development life cycle and accounts for almost one-third of system development costs. In the software industry, testing costs can account for about 35% to 40% of the total…