Safety
A safety property proscribes discrete ''bad things'' from occurring during an execution. A safety property thus characterizes what is permitted by stating what is prohibited. The requirement that the ''bad thing'' be discrete means that a ''bad thing'' occurring during execution necessarily occurs at some identifiable point. Examples of a discrete ''bad thing'' that could be used to define a safety property include: * An execution that starts in a state satisfying a given precondition terminates, but the final state does not satisfy the required postcondition; * An execution of two concurrent processes, where the program counters for both designate statements within a critical section; * An execution of two concurrent processes where each process is waiting for another to change state (known as deadlock). An execution of a program can be described formally by giving the infinite sequence of program states that results as execution proceeds, where the last state for a terminating program is repeated infinitely. For a program of interest, let denote the set of possible program states, denote the set of finite sequences of program states, and denote the set of infinite sequences of program states. Relation holds for sequences and iff is a prefix of or equals . A property of a program is the set of allowed executions. The essential characteristic of a safety property is: If some execution does not satisfy then the defining ''bad thing'' for that safety property occurs at some point in . Notice that after such a ''bad thing'', if further execution results in an execution , then also does not satisfy , since the ''bad thing'' in also occurs in . We take this inference about the irremediability of ''bad things'' to be the defining characteristic for to be a safety property. Formalizing this in predicate logic gives a formal definition for being a safety property. : This formal definition for safety properties implies that if an execution satisfies a safety property then every prefix of (with the last state repeated) also satisfies .Liveness
A liveness property prescribes ''good things'' for every execution or, equivalently, describes something that must happen during an execution. The ''good thing'' need not be discrete —it might involve an infinite number of steps. Examples of a ''good thing'' used to define a liveness property include: * Termination of an execution that is started in a suitable state; * Non-termination of an execution that is started in a suitable state; * Guaranteed eventual entry to a critical section whenever entry is attempted; * Fair access to a resource in the presence of contention. The ''good thing'' in the first example is discrete but not in the others. Producing an answer within a specified real-time bound is a safety property rather than a liveness property. This is because a discrete ''bad thing'' is being proscribed: a partial execution that reaches a state where the answer still has not been produced and the value of the clock (a state variable) violates the bound. Deadlock freedom is a safety property: the "bad thing" is a deadlock (which is discrete). Most of the time, knowing that a program eventually does some "good thing" is not satisfactory; we want to know that the program performs the "good thing" within some number of steps or before some deadline. A property that gives a specific bound to the "good thing" is a safety property (as noted above), whereas the weaker property that merely asserts the bound exists is a liveness property. Proving such a liveness property is likely to be easier than proving the tighter safety property because proving the liveness property doesn't require the kind of detailed accounting that is required for proving the safety property. To differ from a safety property, a liveness property cannot rule out any finite prefix of an execution (since such an would be a "bad thing" and, thus, would be defining a safety property). That leads to defining a liveness property to be a property that does not rule out any finite prefix. : This definition does not restrict a ''good thing'' to being discrete —the ''good thing'' can involve all of , which is an infinite-length execution.History
Lamport used the terms ''safety property'' and ''liveness property'' in his 1977 paper on proving the correctness of multiprocess (concurrent) programs. He borrowed the terms from Petri net theory, which was using the terms ''liveness'' and ''boundedness'' for describing how the assignment of a Petri net's "tokens" to its "places" could evolve; Petri net ''safety'' was a specific form of ''boundedness''. Lamport subsequently developed a formal definition of safety for a NATO short course on distributed systems in Munich. It assumed that properties are invariant under stuttering. The formal definition of safety given above appears in a paper by Alpern and Schneider; the connection between the two formalizations of safety properties appears in a paper by Alpern, Demers, and Schneider. Alpern and Schneider gives the formal definition for liveness, accompanied by a proof that all properties can be constructed using safety properties and liveness properties. That proof was inspired by Gordon Plotkin's insight that safety properties correspond to closed sets and liveness properties correspond to dense sets in a natural topology. Subsequently, Alpern and Schneider not only gave a Büchi automaton characterization for the formal definitions of safety properties and liveness properties but used these automata-formulations to show that verification of safety properties would require anReferences
{{reflist Concurrent computing Theoretical computer science Model checking