By Chao Wang
Abstraction Refinement for giant Scale version Checking summarizes fresh examine on abstraction options for version checking huge electronic procedure. contemplating either the dimensions of brand new electronic platforms and the means of cutting-edge verification algorithms, abstraction is the single possible resolution for the profitable program of version checking suggestions to industrial-scale designs. This e-book describes fresh study advancements in computerized abstraction refinement thoughts. The suite of algorithms awarded during this ebook has tested major development over past artwork; a few of them have already been followed by way of the EDA businesses of their commercial/in-house verification instruments.
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Additional info for Abstraction Refinement for Large Scale Model Checking
One way of finding these subclasses is to classify LTL properties by the strength of the corresponding Biichi automata. According to [BRS99], the strength of a property Biichi automaton can be classified as strong^ weak, and terminal If the property automaton is classified as strong, checking the language emptiness of the composed system requires the evaluation of the general formula EGfair true. Whenever the property automaton is weak or terminal, language emptiness checking in the composed system only requires the evaluation of EFfair or EF EG fair, respectively.
Given a Boolean function, we can build a binary decision tree by obeying a linear order of decision variables; that is, along any path from root to leaf, the variables appear in the same order and no variable appears more than once. We further restrict the form of the decision tree by repeatedly merging any duplicate nodes and removing nodes whose if and else branches are pointing to the same child node. The resulting data structure is a directed acychc graph. Conceptually, this is how we construct the ROBDD for a given Boolean function.
Every unit clause triggers an implication—its only unassigned literal has to be true, otherwise, the clause is no longer satisfiable. The process of applying implications iteratively until no unit clause is left is called Boolean Constrain Propagation (BCP). A decision and the corresponding BCP restrict our attention into a subformula or a subset of the original clauses, since the rest of the clauses have been made true. If we keep making decisions on free variables and performing BCP until no subformula remains to be decided, the formula Symbolic Model Checking 37 is proved to be satisfiable.