Divergence (computer science)

Template:Short description Template:Redirect In computer science, a computation is said to diverge if it does not terminate or terminates in an exceptional state.Template:Rp Otherwise it is said to converge. 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.Template:Sfn

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.Template:Sfn

Denotational semantics

In denotational semantics an object function f : A → B can be modelled as a mathematical function $f:A\cup \{\perp \}\to B\cup \{\perp \}$ 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: $$Clock=tick\to Clock$$ The traces of this process are defined as: $$\mathrm{traces}(Clock)=\{⟨⟩,⟨tick⟩,⟨tick,tick⟩,\dots \}=\{tick{\}}^{*}$$ Now, consider the following process, which hides the tick event of the Clock process: $$P=Clock\setminus tick$$ As $P$ cannot do anything other than perform hidden actions forever, it is equivalent to the process that does nothing but diverge, denoted $𝐝𝐢𝐯$. One semantic model of CSP is the failures-divergences models, which refines the stable failures model by distinguishes processes based on the sets of traces after which they can diverge.

See also

• Infinite loop
• Termination analysis

References

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• J. M. R. Martin and S. A. Jassim (1997). "How to Design Deadlock-Free Networks Using CSP and Verification Tools: A Tutorial Introduction" in Proceedings of the WoTUG-20.

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