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Current hardware security verification processes predominantly rely on manual threat modeling and test plan generation, which are labor-intensive, error-prone, and struggle to scale with increasing design complexity and evolving attack…

Performance optimization of AI infrastructure is key to the fast adoption of large language models (LLMs). The PyTorch compiler (torch.compile), a core optimization tool for deep learning (DL) models (including LLMs), has received due…

Fuzzing is a technique widely used in vulnerability detection. The process usually involves writing effective fuzz driver programs, which, when done manually, can be extremely labor intensive. Previous attempts at automation leave much to…

Automated detection of software vulnerabilities remains a critical challenge in software security. Log4j is an industrial-grade Java logging framework listed as one of the top 100 critical open source projects. On Dec. 10, 2021 a severe…

Natural language elements in source code, e.g., the names of variables and functions, convey useful information. However, most existing bug detection tools ignore this information and therefore miss some classes of bugs. The few existing…

Deep learning (DL) techniques are proven effective in many challenging tasks, and become widely-adopted in practice. However, previous work has shown that DL libraries, the basis of building and executing DL models, contain bugs and can…

Bugs, especially those in concurrent systems, are often hard to reproduce because they manifest only under rare conditions. Testers frequently encounter failures that occur only under specific inputs, even when occurring with low…

The development of machine learning techniques for discovering software vulnerabilities relies fundamentally on the availability of appropriate datasets. The ideal dataset consists of a large and diverse collection of real-world…

The Just-In-Time defect prediction model helps development teams improve software quality and efficiency by assessing whether code changes submitted by developers are likely to introduce defects in real-time, allowing timely identification…

Segment Routing is a modern variant of source routing that is being gradually deployed by network operators. Large ISPs use it for traffic engineering and fast reroute purposes. Its IPv6 dataplane, named SRv6, goes beyond the initial MPLS…

Bug tracking systems play a crucial role in software maintenance, yet developers frequently struggle with low-quality user-submitted reports that omit essential details such as Steps to Reproduce (S2R), Observed Behavior (OB), and Expected…

Automatic detection of software bugs is a critical task in software security. Many static tools that can help detect bugs have been proposed. While these static bug detectors are mainly evaluated on general software projects call into…

For many years, developers could not figure out the mystery of OS kernels. The main source of this mystery is the interaction between operating systems and hardware while system's boot up and kernel initialization. In addition, many…

Bug localization is a crucial aspect of software maintenance, running through the entire software lifecycle. Information retrieval-based bug localization (IRBL) identifies buggy code based on bug reports, expediting the bug resolution…

Read-Copy-Update (RCU) is widely used in the Linux kernel to manage concurrent access to shared data structures.However, improper synchronization when removing RCU protected hash table entries can lead to stale pointers, inconsistent…

One of the most significant challenges in the field of software code auditing is the presence of vulnerabilities in software source code. Every year, more and more software flaws are discovered, either internally in proprietary code or…

Securing operating system (OS) kernel is one central challenge in today's cyber security landscape. The cutting-edge testing technique of OS kernel is software fuzz testing. By mutating the program inputs with random variations for…

In vulnerability detection, machine learning has been used as an effective static analysis technique, although it suffers from a significant rate of false positives. Contextually, in vulnerability discovery, fuzzing has been used as an…

Ideally the variability of a product line is represented completely and correctly by its variability model. However, in practice additional variability is often represented on the level of the build system or in the code. Such a situation…

Increased attention to RISC-V in Cloud, Data Center, Automotive and Networking applications, has been fueling the move of RISC-V to the high-performance computing scenario. However, lack of powerful performance monitoring tools will result…