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In
model checking In computer science, model checking or property checking is a method for checking whether a finite-state model of a system meets a given specification (also known as correctness). This is typically associated with hardware or software systems ...
, the Metric Interval Temporal Logic (MITL) is a fragment of
Metric Temporal Logic Metric temporal logic (MTL) is a special case of temporal logic. It is an extension of temporal logic in which temporal operators are replaced by time-constrained versions like ''until'', ''next'', ''since'' and ''previous'' operators. It is a linea ...
(MTL). This fragment is often preferred to MTL because some problems that are undecidable for MTL become decidable for MITL.


Definition

A MITL formula is an MTL formula, such that each set of reals used in subscript are intervals, which are not singletons, and whose bounds are either a natural number or are infinite.


Difference from MTL

MTL can express a statement such as the sentence S: "P held exactly ten time units ago". This is impossible in MITL. Instead, MITL can say T: "P held between 9 and 10 time units ago". Since MITL can express T but not S, in a sense, MITL is a restriction of MTL which allows only less precise statements.


Problems that MITL avoids

One reason to want to avoid a statement such as S is that its truth value may change an arbitrary number of times in a single time unit. Indeed, the truth value of this statement may change as many times as the truth value of P change, and P itself may change an arbitrary number of time in a single time unit. Let us now consider a system, such as a
timed automaton In automata theory, a timed automaton is a finite automaton extended with a finite set of real-valued clocks. During a run of a timed automaton, clock values increase all with the same speed. Along the transitions of the automaton, clock values can ...
or a
signal automaton In automata theory, a field of computer science, a signal automaton is a finite automaton extended with a finite set of real-valued clocks. During a run of a signal automaton, clock values increase all with the same speed. Along the transitions of ...
, which want to know at each instant whether S holds or not. This system should recall everything that occurred in the last 10 time units. As seen above, it means that it must recall an arbitrarily large number of events. This can not be implemented by a system with finite memory and clocks.


Bounded variability

One of the main advantage of MITL is that each operator has the bounded variability property. Example: Given the statement T defined above. Each time the truth value of T switches from false to true, it remains true for at least one time unit. Proof: At a time t where T becomes true, it means that: * between 9 and 10 time units ago, P was true. * just before time t, P was false. Hence, P was true exactly 9 time units ago. It follows that, for each t'\in ,1/math>, at time t+t', P was true 9+t' time units ago. Since 9+t'\in
,10 This list contains selected positive numbers in increasing order, including counts of things, dimensionless quantity, dimensionless quantities and probability, probabilities. Each number is given a name in the Long and short scales, short scale ...
/math>, at time t', T holds. A system, at each instant, wants to know the value of T. Such a system must recall what occurred during the last ten time units. However, thanks to the bounded variability property, it must recall at most 10 time units when T becomes true. And hence 11 times when T becomes false. Thus this system must recall at most 21 events, and hence can be implemented as a
timed automaton In automata theory, a timed automaton is a finite automaton extended with a finite set of real-valued clocks. During a run of a timed automaton, clock values increase all with the same speed. Along the transitions of the automaton, clock values can ...
or a
signal automaton In automata theory, a field of computer science, a signal automaton is a finite automaton extended with a finite set of real-valued clocks. During a run of a signal automaton, clock values increase all with the same speed. Along the transitions of ...
.


Examples

Examples of MITL formulas: * \square\diamond_p states that the letter p appears at least once in each open interval of length 1. * \triangleright_p where \triangleright_p is the prophecy operator defined as \square_\neg p\land\diamond_p and which states that the first occurrence of p in the future is in i time unit. * p\land\square(p\implies\triangleright_p) states that p holds exactly at each integral time and not anytime else.


Fragments


Safety-MTL0,∞

The fragment Safety-MTL0,v is defined as the subset of MITL0,∞ containing only formulas in positive normal form where the interval of every until operator has an upper bound. For example, the formula \Box(a\implies\Diamond_b) which states that each a is followed, less than one time unit later, by a b, belongs to this logic.


Open and closed MITL

The fragment Open-MTL contains the formula in positive normal form such that: * for each \mathcal U_I, I is open, and * for each \mathcal R_I, I is closed. The fragment ''Closed-MITL'' contains the negation of formulas of ''Open-MITL''.


Flat and Coflat MITL

The fragment Flat-MTL contains the formula in positive normal form such that: * for each \phi_1\mathcal U_I\phi_2, if I is unbounded, then \phi_1 is a LTL-formula * for each \phi_1\mathcal R_I\phi_2, if I is unbounded, then \phi_2 is a LTL-formula The fragment Coflat-MITL contains the negation of formulas of ''Flat-MITL''.


Non-strict variant

Given any fragment ''L'', the fragment ''Lns'' is the restriction of ''L'' in which only non strict operators are used.


MITL0,∞ and MITL0

Given any fragment ''L'', the fragment ''L0,∞'' is the subset of ''L'' where the lower bound of each interval is 0 or the upper bound is infinity. Similarly we denote by ''L0'' (respectively, ''L'') the subset of ''L'' such that the lower bound of each interval is 0 (respectively, the upper bound of each interval is ∞).


Expressiveness over signals

Over
signals In signal processing, a signal is a function that conveys information about a phenomenon. Any quantity that can vary over space or time can be used as a signal to share messages between observers. The ''IEEE Transactions on Signal Processing'' ...
, MITL0 is as expressive as MITL. This can be proven by applying the following rewriting rules to a MITL formula. * \phi\mathcal U_\psi is equivalent to \Box_\phi\mathcal U\psi\land\Diamond_\psi (the construction for half-closed and closed intervals is similar). * \Diamond_\phi is equivalent to \Diamond_\Box_\Diamond_\phi if 2a-b\ge0. * \Diamond_\phi is equivalent to \Diamond_\Diamond_\phi if a. * \Diamond_\phi is equivalent to \Box_\Diamond\phi. Applying those rewriting rules exponentially increases the size of the formula. Indeed, the numbers a and b are traditionally written in binary, and those rules should be applied O\left(\frac\right) times.


Expressiveness over timed words

Contrary to the case of signals, MITL is strictly more expressive than MITL0,∞. The rewriting rules given above do not apply in the case of timed words because, in order to rewrite \Diamond_ the assumption must be that some event occurs between times 0 and a, which is not necessarily the case.


Satisfiability problem

The problem of deciding whether a MITL formula is satisfiable over a signal is in PSPACE-complete.


References needed

R. Alur, T. Feder, and T.A. Henzinger. The Benefits of Relaxing Punctuality. Journal of the ACM, 43(1):116–146, 1996. R. Alur and T.A. Henzinger. Logics and Models of Real-Time: A Survey. In Proc. REX Workshop, Real-time: Theory in Practice, pages 74–106. LNCS 600, Springer, 1992. T.A. Henzinger. It's about Time: Real-time Logics Reviewed. In Proc. CONCUR'98, pages 439–454. LNCS 1466, Springer, 1998.


References

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Temporal logic Model checking