Divergence (computer science)

In computer science, a computation is said to diverge if it does not terminate or terminates in an exceptional state. Otherwise it is said to converge.[citation needed] In domains where computations are expected to be infinite, such as process calculi, a computation is said to diverge if it fails to be productive (i.e. to continue producing an action within a finite amount of time).

Definitions

Various subfields of computer science use varying, but mathematically precise, definitions of what it means for a computation to converge or diverge.

Rewriting

In abstract rewriting, an abstract rewriting system is called convergent if it is both confluent and terminating.

The notation t ↓ n means that t reduces to normal form n in zero or more reductions, t↓ means t reduces to some normal form in zero or more reductions, and t↑ means t does not reduce to a normal form; the latter is impossible in a terminating rewriting system.

In the lambda calculus an expression is divergent if it has no normal form.

Denotational semantics

In denotational semantics an object function f : A → B can be modelled as a mathematical function where ⊥ (bottom) indicates that the object function or its argument diverges.

Concurrency theory

In the calculus of communicating sequential processes (CSP), divergence occurs when a process performs an endless series of hidden actions. For example, consider the following process, defined by CSP notation: The traces of this process are defined as: Now, consider the following process, which hides the tick event of the Clock process: As cannot do anything other than perform hidden actions forever, it is equivalent to the process that does nothing but diverge, denoted . One semantic model of CSP is the failures-divergences model, which refines the stable failures model by distinguishing processes based on the sets of traces after which they can diverge.

See also

Notes

  1. ↑ Hoare 1969, p. 377.
  2. ↑ Baader & Nipkow 1998, p. 9.
  3. ↑ Pierce 2002, p. 65.
  4. ↑ Roscoe 2010.

References

Bibliography

Martin, J. M. R.; Jassim, S. A. (1997). "How to Design Deadlock-Free Networks Using CSP and Verification Tools: A Tutorial Introduction". In Bakkers, André W. P. (ed.). Parallel Programming and Java: Proceedings of WoTUG-20. WoTUG-20. Amsterdam: IOS Press. Archived from the original on 8 July 2022.{{cite conference}}: CS1 maint: miscellaneous url (link)