相关论文: Tracing Vulnerable Code Lineage
Security vulnerabilities present in a code that has been written in diverse programming languages are among the most critical yet complicated aspects of source code to detect. Static analysis tools based on rule-based patterns usually do…
Over the past few years, deep learning methods have been applied for a wide range of Software Engineering (SE) tasks, including in particular for the important task of automatically predicting and localizing faults in software. With the…
For teams using distributed version control systems, the right collaborative development workflows can help maintaining the long-term quality of project repositories and improving work efficiency. Despite the fact that the workflows are…
The security of research software is essential for ensuring the integrity and reproducibility of scientific results. However, research software security is still largely unexplored. Due to its dependence on open source components and…
This article presents a study on the quality and execution of research code from publicly-available replication datasets at the Harvard Dataverse repository. Research code is typically created by a group of scientists and published together…
Python applications depend on third-party native libraries that may be vendored within package distributions or installed on the host system. When vulnerabilities are discovered in these native libraries, determining which Python packages…
Binary code similarity approaches compare two or more pieces of binary code to identify their similarities and differences. The ability to compare binary code enables many real-world applications on scenarios where source code may not be…
Many open source software (OSS) projects need more human resources for maintenance, improvements, and sometimes even their survival. These needs allegedly apply even to vital OSS projects that can be seen as being a part of the world's…
We introduce Repro, an open-source library which aims at improving the reproducibility and usability of research code. The library provides a lightweight Python API for running software released by researchers within Docker containers which…
Bug reports are common artefacts in software development. They serve as the main channel for users to communicate to developers information about the issues that they encounter when using released versions of software programs. In the…
Increased reproducibility of machine learning research has been a driving force for dramatic improvements in learning performances. The scientific community further fosters this effort by including reproducibility ratings in reviewer forms…
One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. These flaws are highly likely ex-ploited and lead to system compromise, data leakage, or denial of…
Assessing similarity in source code has gained significant attention in recent years due to its importance in software engineering tasks such as clone detection and code search and recommendation. This work presents a comparative analysis…
The Open-Source Software community has become the center of attention for many researchers, who are investigating various aspects of collaboration in this extremely large ecosystem. Due to its size, it is difficult to grasp whether or not…
[Background] In large open-source software projects, development knowledge is often fragmented across multiple artefacts and contributors such that individual stakeholders are generally unaware of the full breadth of the product features.…
Due to the inherent immutability of blockchain technology, smart contract updates require their deployment at new addresses rather than modifying existing ones, thus fragmenting version histories and creating critical blind spots for…
Web applications continue to be a favorite target for hackers due to a combination of wide adoption and rapid deployment cycles, which often lead to the introduction of high impact vulnerabilities. Static analysis tools are important to…
Large language models (LLMs) have developed rapidly in recent years, revolutionizing various fields. Despite their widespread success, LLMs heavily rely on external code dependencies from package management systems, creating a complex and…
The security guarantee of AI-enabled software systems (particularly using deep learning techniques as a functional core) is pivotal against the adversarial attacks exploiting software vulnerabilities. However, little attention has been paid…
Modern software heavily relies on the use of components. Those components are usually published in central repositories, and managed by build systems via dependencies. Due to issues around vulnerabilities, licenses and the propagation of…