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Start of ModelChecking chapter
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@ -1053,6 +1053,62 @@ The reader may be worried at this point that coming up with invariants can be ra
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In the next chapter, we meet a technique for finding invariants automatically, in some limited but important circumstances.
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In the next chapter, we meet a technique for finding invariants automatically, in some limited but important circumstances.
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\chapter{Model Checking}
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Our analyses so far have been tedious for at least two different reasons.
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First, we've hand-crafted definitions of transition systems, rather than just writing programs in conventional programming languages.
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The next chapter will clear that obstacle, by introducing operational semantics, for building transition systems automatically from programs.
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The other inconvenience we've faced is defining invariants manually.
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There isn't a silver bullet to get us out of this duty, when working with Turing-complete languages\index{Turing-completeness}, where almost all interesting questions, this one included, are undecidable.
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However, when we can phrase problems in terms of transition systems with \emph{finitely many reachable states}, we can construct invariants automatically by \emph{exhaustive exploration of the state space}, an approach otherwise known as \emph{model checking}\index{model checking}.
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Surprisingly many real programs can be reduced to finite state spaces, using the techniques introduced in this chapter.
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First, though, let's formalize our intuitions about exhaustive state-space exploration as a sound way to find invariants.
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\section{Exhaustive Exploration}
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For an arbitrary binary relation $R$, we write $R^n$ for the $n$-times self-composition of $R$\index{self-composition of relations}.
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Formally, where $\mathsf{id}$ is the identity relation\index{identity relation} that only relates values to themselves, we have:
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\begin{eqnarray*}
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R^0 &=& \mathsf{id} \\
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R^{n+1} &=& R \circ R^n
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\end{eqnarray*}
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For some set $S$ and binary relation $R$, we also write $R(S)$ for the composition of $R$ and $S$\index{composition of a relation and a set}, namely $\{x \mid \exists y \in S. \; y \; R \; x\}$.
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\newcommand{\ns}[0]{\hspace{-.05in}}
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Which states of transition system $\angled{S, S_0, \to}$ are reachable after 0 steps?
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That would be precisely the initial states $S_0$, which we can also write as $\to^0\ns(S_0)$.
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Which states are reachable after exactly 1 step?
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That is $\to\ns(S_0)$, or $\to^1\ns(S_0)$.
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How about 2, 3, and 4 steps?
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There we have $\to^2\ns(S_0)$, $\to^3\ns(S_0)$, and $\to^4\ns(S_0$).
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It follows that the set of states reachable after $n$ steps is:
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\begin{eqnarray*}
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\mathsf{reach}(n) &=& \bigcup_{i < n} \to^i\ns(S_0)
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\end{eqnarray*}
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This iteration process is not obviously executable yet, because, a priori, we seem to need to consider all possible $n$ values, to characterize the state space fully.
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However, a crucial property allows us to terminate our search soundly under some conditions.
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\begin{theorem}
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\invariants
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If $\mathsf{reach}(n+1) = \mathsf{reach}(n)$ for some $n$, then $\mathsf{reach}(n)$ is an invariant of the system.
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\end{theorem}
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Here we call $\mathsf{reach}(n)$ a \emph{fixed point}\index{fixed point} of the transition system, because it is closed under further exploration.
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To find a fixed point with a concrete system, we start with $S_0$.
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We repeatedly take the \emph{single-step closure}\index{single-step closure} corresponding to composition with $\to$.
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At each step, we check whether the expanded set is actually equal to the previous set.
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If so, our process of \emph{multi-step closure}\index{multi-step closure} has terminated, and we have an invariant, by construction.
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Again, keep in mind that multi-step closure will not terminate for most transition systems, and there is an art to phrasing a problem in terms of systems where it \emph{will} terminate.
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\appendix
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\appendix
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