
MoXIchecker is an extensible model-checking framework for the intermediate modeling language MoXI (Model eXchange Interlingua). The tool is written in Python and can easily incorporate new model-checking algorithms. Currently, it supports theories of QF_BV, QF_ABV, QF_LIA, QF_NIA, QF_LRA, and QF_NRA. Setup MoXIchecker relies on Python 3.10 (or newer) and uses PySMT for manipulating and solving SMT formulas. We recommend MathSAT and Z3 as the backend SMT solvers, as they work best from our experience. To setup the environment to execute MoXIchecker, run the following commands: pip install pysmt==0.9.6 pysmt-install --msat --z3 Usage To verify whether the query (defined in check-system) is reachable in the system (defined in define-system) of a MoXI model (in JSON format), run: ./bin/moxichecker # e.g., examples/QF_ABV/count2.moxi.json Please refer to ./bin/moxichecker -h for more information. License MoXIchecker is licensed under the Apache License 2.0.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
