English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

We present a straightforward source-to-source transformation that introducesjustifications for user-defined constraints into the CHR programming language.Then a scheme of two rules suffices to allow for logical retraction (deletion,removal) of constraints during computation. Without the need to recompute fromscratch, these rules remove not only the constraint but also undo allconsequences of the rule applications that involved the constraint. We prove aconfluence result concerning the rule scheme and show its correctness. Whenalgorithms are written in CHR, constraints represent both data and operations.CHR is already incremental by nature, i.e. constraints can be added at runtime.Logical retraction adds decrementality. Hence any algorithm written in CHR withjustifications will become fully dynamic. Operations can be undone and data canbe removed at any point in the computation without compromising the correctnessof the result. We present two classical examples of dynamic algorithms, writtenin our prototype implementation of CHR with justifications that is availableonline: maintaining the minimum of a changing set of numbers and shortest pathsin a graph whose edges change.

Justifications in Constraint Handling Rules for Logical Retraction in Dynamic Algorithms