As we mentioned, temporal logic comes in a number of flavors. At present we deal only with

*Linear Temporal Logic (LTL)*. It is

*linear*because we evaluate each LTL formula with respect to a vertex-labeled infinite path p

_{0}p

_{1}..., where each vertex p

_{i}in the path corresponds to a point in time. "Present" is p

_{0}. "Future" is any of p

_{i}with i ≥ 0. Each vertex is labeled by a subset of 2

^{Σ}where Σ is a set of

*atomic propositions*. In other words, the label of a vertex indicates which atomic propositions are

*true*in that vertex. Here is a somewhat contrived example. Suppose that Σ = {a,b}. As an example, take the path {a}

^{2000}{a,b}

^{ω}, which is a path whose first 2000 vertices are {a}-labeled and the rest of the vertices are {a,b}-labeled. An example of an LTL formula is "at some point in the future, 'b' holds", which is true. Another example is "a holds until b holds", which is also true.

More formally, the syntax of LTL formulas can be defined in Backus-Naur form as follows:

φ, ψ := p (p ∈ Σ) | φ ∧ ψ | ¬ φ | X φ | φ U ψ

Given a 2

^{Σ}-labeled (infinite) path w, we write w

^{i}to refer to the infinite subpath of w starting from the ith vertex (the initial vertex is the 0th vertex). We may now define the semantics of LTL formulas:

- w |= p (p ∈ Σ) if the label of the initial vertex of w contains p

- w |= φ ∧ ψ if w |= φ and w |= ψ

- w |= ¬ φ if it is not the case that w |= φ

- w |= X φ if w
^{1}|= φ

- w |= φ U ψ if there exists j ≥ 0 such that w
^{j}|= ψ and for all 0 ≤ i < j, we have w^{i}|= φ

We use F φ to abbreviate "true U φ", which says that φ holds in some future. Note that "future" also includes the present. We use G φ to abbreviate ¬ F ¬ φ, which says that φ must hold at all points in the path, i.e.,

*globally*. Finally, note that {¬,∧} captures all other boolean connectives, which allows us to freely use any boolean connectives when we write formulas.

How do we use LTL to verify real world systems? The answer requires that we first define the semantics of LTL formulas with respect to

*Kripke Structures*. A

*Kripke structure*K over a finite alphabet Σ is a tuple (S,E,λ: S -> 2

^{Σ}), where S is a set of vertices (or

*states*)and E a set of directed edges on S. It is normally assumed that each vertex in S has at least one outgoing edge. The function λ defines which propositions in Σ are true in a given state. The reader should convince himself that the notion of Kripke structures can be used to model many practical systems. You can first start with traffic lights, in which case &Sigma = {green,red,yellow}, S consists of three states (each corresponding to the event where the light is green, red, or yellow), and E models how traffic lights work (e.g. green -> yellow -> red). A more interesting example includes Dijkstra's algorithm for the dining philosopher problem.

Now, given a state s in structure K, we may define the semantics of LTL formulas: K,s |= φ if for all directed path w in K starting from s, we have w |= φ. For example, if K models traffic lights, then the formulas G( green -> F red ) and G( green -> X yellow ) have to hold in every state of K. [For example, the first formula says that, it is globally true that if the light is presently green, then at some point in the future it will turn red.]

What we are interested in is an algorithm that solves the following model-checking problem: given a Kripke structure K over Σ, a state s in K, and an LTL formula φ over Σ, decide whether K,s |= φ. The problem is PSPACE-complete. The best known algorithm, which runs in 2

^{O(|φ|)}x |K|, was given by Vardi and Wolper by utilizing automata theory on infinite strings. Although the complexity of the algorithm is exponential in the size of the formula, the algorithm runs quite fast in practice because practical specifications are usually short. We shall talk about this algorithm in the near future.

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