Project description
How to assess quantitative hyperproperties between software
The rapid and widespread integration of modern software systems has led to the development of a multitude of varied systems that offer vastly different levels of robustness, reliability and efficiency even for the same tasks. This has led to a growing need to evaluate different implementations and capture their quantitative differences; despite this, there is a distinct lack of tools for this purpose. With the support of the Marie Skłodowska-Curie Actions programme, the QHyperSTAR project will develop a framework for quantitative hyperproperties (QHPs) to assess and score different implementations. Further, the framework will provide safety and liveness classifications of QHPs, algorithms for memory-efficient runtime monitoring and a comprehensive specification language for automated analysis.
Objective
Modern software systems underpin critical infrastructure from aviation to healthcare. Their reliability depends not only on whether requirements are met, but also on how well they are met. Two flight controllers may both ensure safety yet differ in robustness to turbulence; two medical devices may both function yet differ in how much information they leak. Boolean hyperproperties relate multiple executions to specify correctness of implementations, but cannot capture their quantitative differences. As the societal importance of software grows, engineers and regulators need tools to measure and compare implementations.
The QHyperSTAR project addresses this gap by developing the first formal framework for quantitative hyperproperties (QHPs), which assign numerical scores to implementations based on relations across executions. QHyperSTAR pursues three objectives: (1) a safety-liveness classification of QHPs that reflects their verification complexity, (2) an expressive specification language supporting automated analysis, and (3) memory-efficient runtime monitoring algorithms validated on resource-constrained cyber-physical systems.
The main outcomes are a safety-liveness decomposition of QHPs, a specification language with clear complexity results, and an open-source monitoring prototype. By making requirements such as robustness and privacy measurable and automatically analyzable, QHyperSTAR advances formal methods and enables more reliable digital technologies.
Under Prof. Finkbeiner’s supervision at CISPA, I will benefit from a strong synergy with the ERC project HYPER, which lays the foundations of boolean hyperproperties, while QHyperSTAR establishes the complementary quantitative axis. In return, by providing the missing infrastructure for QHPs, I will elevate the impact of the group’s successful monitoring framework RTLola. This environment will let me deepen my expertise, expand collaborations, and develop leadership skills for a research career in Europe.
Fields of science (EuroSciVoc)
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
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(opens in new window) HORIZON-MSCA-2025-PF
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66123 SAARBRUCKEN
Germany
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