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Static analysis is a powerful tool for detecting security vulnerabilities and other programming problems. Global taint tracking, in particular, can spot vulnerabilities arising from complicated data flow across multiple functions. However,…

Large language models (LLMs) are widely used in software development. However, the code generated by LLMs often contains vulnerabilities. Several secure code generation methods have been proposed to address this issue, but their current…

In the open source software (OSS) ecosystem, there exists a complex software supply chain, where developers upstream and downstream widely borrow and reuse code. This results in the widespread occurrence of recurring defects, missing fixes,…

The widespread adoption of open-source ecosystems enables developers to integrate third-party packages, but also exposes them to malicious packages crafted to execute harmful behavior via public repositories such as PyPI. Existing datasets…

Evaluating the correctness of code generated by AI is a challenging open problem. In this paper, we propose a fully automated method, named ACCA, to evaluate the correctness of AI-generated code for security purposes. The method uses…

Code analysis is fundamental in Software Engineering, supporting debugging, optimization, and security assessment. Human developers approach it through syntax parsing, static semantics inference, and dynamic reasoning. Traditional tools are…

While hardware generators have drastically improved design productivity, they have introduced new challenges for the task of verification. To effectively cover the functionality of a sophisticated generator, verification engineers require…

Static bug detection tools help developers detect problems in the code, including bad programming practices and potential defects. Recent efforts to integrate static bug detectors in modern software development workflows, such as in code…

Feature extraction and feature selection are the first tasks in pre-processing of input logs in order to detect cyber security threats and attacks while utilizing machine learning. When it comes to the analysis of heterogeneous data derived…

The current cybersecurity landscape is increasingly complex, with traditional Static Application Security Testing (SAST) tools struggling to capture complex and emerging vulnerabilities due to their reliance on rule-based matching.…

Over the years, open-source software systems have become prey to threat actors. Even as open-source communities act quickly to patch the breach, code vulnerability screening should be an integral part of agile software development from the…

Open-source software vulnerability patch detection is a critical component for maintaining software security and ensuring software supply chain integrity. Traditional manual detection methods face significant scalability challenges when…

Test case generation (TCG) for Python poses distinctive challenges due to the language's dynamic nature and the absence of strict type information. Previous research has successfully explored automated unit TCG for Python, with solutions…

Python has emerged as one of the most popular programming languages, extensively utilized in domains such as machine learning, data analysis, and web applications. Python's dynamic nature and extensive usage make it an attractive candidate…

Python, one of the most prevalent programming languages today, is widely utilized in various domains, including web development, data science, machine learning, and DevOps. Recent scholarly efforts have proposed a methodology to assess…

Graph domain adaptation has emerged as a promising approach to facilitate knowledge transfer across different domains. Recently, numerous models have been proposed to enhance their generalization capabilities in this field. However, there…

This paper presents the source code analysis of a file reader server socket program (connection-oriented sockets) developed in Java, to illustrate the identification, impact analysis and solutions to remove five important software security…

Tests that cause spurious failures without any code changes, i.e., flaky tests, hamper regression testing, increase maintenance costs, may shadow real bugs, and decrease trust in tests. While the prevalence and importance of flakiness is…

In modern software development, vulnerability detection is crucial due to the inevitability of bugs and vulnerabilities in complex software systems. Effective detection and elimination of these vulnerabilities during the testing phase are…

Static code analysis tools are designed to aid software developers to build better quality software in less time, by detecting defects early in the software development life cycle. Even the most experienced developer regularly introduces…