QFM 2012 - 1st Workshop on Quantities in Formal Methods (QFM 2012)
Topics/Call fo Papers
1st Workshop on Quantities in Formal Methods (QFM 2012)
Organizers: Axel Legay and Uli Fahrenberg, Irisa / INRIA Rennes, France, Claus Thrane, Aalborg U, Denmark
This workshop will focus on quantities in modeling, verification, and synthesis. Modern applications of formal methods require to reason formally on quantities such as time, resources, or probabilities. Standard formal methods and tools have gotten very good at modeling (and verifying) qualitative properties: whether or not certain events will occur. During the last years, these methods and tools have been extended to also cover quantitative aspects, notably leading to tools like e.g. UPPAAL (for real-time systems), PRISM (for probabilistic systems), and PHAVer (for hybrid systems). A lot of work remains to be done however before these tools can be used in the industrial applications at which they are aiming. Particular issues are as follows:
- Almost all current methods and tools are not robust, in the sense that small changes in the quantitative inputs (e.g. due to measurement errors) can lead to large changes in the verification result. This is not desirable, and fixing it requires a paradigm switch away from the Boolean verification domain to real-valued domains.
- Most currently used algorithms for quantitative verification (and synthesis) are not efficient enough and do not scale well for industrial-size systems. New approaches, such as e.g. simulation-based statistical model checking, seem promising in this regard; but it is an open question how to apply them to synthesis.
- Almost all current methods and tools focus on only one quantitative aspect: either time, or resources, or probabilities. Integration of these formalisms is an active research area.
Organizers: Axel Legay and Uli Fahrenberg, Irisa / INRIA Rennes, France, Claus Thrane, Aalborg U, Denmark
This workshop will focus on quantities in modeling, verification, and synthesis. Modern applications of formal methods require to reason formally on quantities such as time, resources, or probabilities. Standard formal methods and tools have gotten very good at modeling (and verifying) qualitative properties: whether or not certain events will occur. During the last years, these methods and tools have been extended to also cover quantitative aspects, notably leading to tools like e.g. UPPAAL (for real-time systems), PRISM (for probabilistic systems), and PHAVer (for hybrid systems). A lot of work remains to be done however before these tools can be used in the industrial applications at which they are aiming. Particular issues are as follows:
- Almost all current methods and tools are not robust, in the sense that small changes in the quantitative inputs (e.g. due to measurement errors) can lead to large changes in the verification result. This is not desirable, and fixing it requires a paradigm switch away from the Boolean verification domain to real-valued domains.
- Most currently used algorithms for quantitative verification (and synthesis) are not efficient enough and do not scale well for industrial-size systems. New approaches, such as e.g. simulation-based statistical model checking, seem promising in this regard; but it is an open question how to apply them to synthesis.
- Almost all current methods and tools focus on only one quantitative aspect: either time, or resources, or probabilities. Integration of these formalisms is an active research area.
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Last modified: 2011-12-20 18:27:22