
doi: 10.1109/mdso.2006.47
Model checking is rather poor when properties deal not with causality of events but with data types or recursive constructs. In that area, algebraic methods, even if they're more complex to grasp, are much more appropriate and efficient. And it's true that, with Petri nets, you can do both model checking and a sort of parameterized analysis. But, if model checking remains as efficient as what you can get from a Promela program, the model itself only offers basic constructs to handle parallelism. This is also true with parameterized proofs using Petri net invariants
[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH], [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]
[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH], [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]
| 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 |
