Related papers: Lessons Learned From Microkernel Verification -- S…

Many fields of science rely on software systems to answer different research questions. For valid results researchers need to trust the results scientific software produces, and consequently quality assurance is of utmost importance. In…

Scientific machine learning (SciML) models are transforming many scientific disciplines. However, the development of good modeling practices to increase the trustworthiness of SciML has lagged behind its application, limiting its potential…

Software engineers integrate third-party components into their applications. The resulting software supply chain is vulnerable. To reduce the attack surface, we can verify the origin of components (provenance) before adding them.…

As advanced machine learning systems' capabilities begin to play a significant role in geopolitics and societal order, it may become imperative that (1) governments be able to enforce rules on the development of advanced ML systems within…

A self-healing software system is an advanced computer program or system designed to detect, diagnose, and automatically recover from faults or errors without human intervention. These systems are typically employed in mission-critical…

Fully automated verification of large-scale software and hardware systems is arguably the holy grail of formal methods. Large language models (LLMs) have recently demonstrated their potential for enhancing the degree of automation in formal…

Robotic systems are complex and safety-critical software systems. As such, they need to be tested thoroughly. Unfortunately, robot software is intrinsically hard to test compared to traditional software, mainly since the software needs to…

Formal verification offers a path to provably correct software, but writing verified code remains expensive enough that the technique is rarely used in production. Recent large language models can accelerate this work, and recent benchmarks…

The requirements in automation, digitalization, and fast computations have loaded the IT sector with expectations of highly reliable, efficient, and cost-effective software. Given that the process of testing, verification, and validation of…

Quantum computers promise to efficiently solve not only problems believed to be intractable for classical computers, but also problems for which verifying the solution is also considered intractable. This raises the question of how one can…

The mass production of complex software has made it impossible to manually test it for security vulnerabilities. Automated security testing tools come in a variety of flavors, function at various stages of software development, and target…

Real-world software applications must constantly evolve to remain relevant. This evolution occurs when developing new applications or adapting existing ones to meet new requirements, make corrections, or incorporate future functionality.…

OpenACC is a high-level directive-based parallel programming model that can manage the sophistication of heterogeneity in architectures and abstract it from the users. The portability of the model across CPUs and accelerators has gained the…

This note concerns a search for publications in which the pragmatic concept of a test as conducted in the practice of software testing is formalized, a theory about software testing based on such a formalization is presented or it is…

Today's software systems like cyber-physical production systems or big data systems have to process large volumes and diverse types of data which heavily influences the quality of these so-called data-intensive systems. However, traditional…

Despite multiprocessors implementing weak memory models, verification methods often assume Sequential Consistency (SC), thus may miss bugs due to weak memory. We propose a sound transformation of the program to verify, enabling SC tools to…

Software testing plays a critical role in ensuring that systems behave as intended. However, existing automated testing approaches struggle to match the capabilities of human engineers due to key limitations such as test locality, lack of…

Cyber-physical systems (CPS) such as autonomous cars, aircraft, and robots are often also safety-critical; thus it is imperative that they operate as intended with a high degree of certainty. Formal verification has been employed to verify…

Traditionally, practitioners use formal methods pre-dominately for one half of the quality-assurance process: verification (do we build the software right?). The other half -- validation (do we build the right software?) -- has been given…

In recent years, machine learning has demonstrated impressive results in various fields, including software vulnerability detection. Nonetheless, using machine learning to identify software vulnerabilities presents new challenges,…