相关论文: Compatible Remediation on Vulnerabilities from Thi…

Increasing complexity in software systems places a growing demand on reasoning tools that unlock vulnerabilities manifest in source code. Many current approaches focus on vulnerability analysis as a classifying task, oversimplifying the…

Modern software systems rely on dependency networks of reusable libraries, where breaking changes propagate and cause downstream consumers to fail. Despite growing research across ecosystems, no comprehensive synthesis exists. We conduct a…

Background: Code cloning - copying and reusing pieces of source code - is a common phenomenon in software development in practice. There have been several empirical studies on the effects of cloning, but there are contradictory results…

Software bugs significantly contribute to software cost and increase the risk of system malfunctioning. In recent years, many automated program-repair approaches have been proposed to automatically fix undesired program behavior. Despite of…

(Note: This work is a preprint.) Static analysis (SA) tools produce many diagnostic alerts indicating that source code in C or C++ may be defective and potentially vulnerable to security exploits. Many of these alerts are false positives.…

Code readability and software complexity are important software quality metrics that impact other software metrics such as maintainability, reusability, portability and reliability. This paper presents an empirical study of the…

While most forks on platforms like GitHub are short-lived and used for social collaboration, a smaller but impactful subset evolve into long-lived forks, referred to here as variants, that maintain independent development trajectories.…

High-performance computing often relies on parallel programming models such as MPI for distributed-memory systems. While powerful, these models are prone to subtle programming errors, leading to development of multiple correctness checking…

The identification of vulnerabilities is a continuous challenge in software projects. This is due to the evolution of methods that attackers employ as well as the constant updates to the software, which reveal additional issues. As a…

This paper introduces an innovative approach that combines Large Language Models (LLMs) with Formal Verification strategies for automatic software vulnerability repair. Initially, we employ Bounded Model Checking (BMC) to identify…

Identifying which software versions are affected by a vulnerability is critical for patching, risk mitigation. Despite a growing body of tools, their real-world effectiveness remains unclear due to narrow evaluation scopes often limited to…

Early identification of security issues in software development is vital to minimize their unanticipated impacts. Code review is a widely used manual analysis method that aims to uncover security issues along with other coding issues in…

Background. Developers use Automated Static Analysis Tools (ASATs) to control for potential quality issues in source code, including defects and technical debt. Tool vendors have devised quite a number of tools, which makes it harder for…

Assessing the security posture of modern computing systems typically requires the use of multiple specialized tools. These tools focus on different aspects such as configuration compliance, file integrity, and vulnerability exposure, and…

[Context:] The acceptance of candidate patches in automated program repair has been typically based on testing oracles. Testing requires typically a costly process of building the application while ML models can be used to quickly classify…

Cooperative multi-agent learning plays a crucial role for developing effective strategies to achieve individual or shared objectives in multi-agent teams. In real-world settings, agents may face unexpected failures, such as a robot's leg…

Large Language Models (LLMs) like LLaMA, Mistral, and Gemma are increasingly used in decision-critical domains such as healthcare, law, and finance, yet their reliability remains uncertain. They often make overconfident errors, degrade…

The relentless process of tracking and remediating vulnerabilities is a top concern for cybersecurity professionals. The key challenge is trying to identify a remediation scheme specific to in-house, organizational objectives. Without a…

Large language models (LLMs) rely on internal knowledge to solve many downstream tasks, making it crucial to keep them up to date. Since full retraining is expensive, prior work has explored efficient alternatives such as model editing and…

Software Bills of Material (SBOMs) are becoming a consolidated, often enforced by governmental regulations, way to describe software composition. However, based on recent studies, SBOMs suffer from limited support for their consumption and…