Inductive programming: Difference between revisions

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{{Short description|Area of automatic programming}}

{{Programming paradigms}}

'''Inductive programming''' ('''IP''') is a special area of [[automatic programming]], covering research from [[artificial intelligence]] and [[Computer programming|programming]], which addresses [[machine learning|learning]] of typically [[declarative programming|declarative]] ([[logic programming|logic]] or [[functional programming|functional]]) and often [[recursion|recursive]] programs from incomplete specifications, such as input/output examples or constraints.

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|journal=Computational Intelligence

|volume=30|issue=3|pages=473–513|year=2014

|doi=10.1111/coin.12004|doi-access=free|hdl=10251/34946|hdl-access=free}}

</ref> abstraction has also been explored as a more powerful approach to [[cumulative learning]] and function invention.<ref>

{{cite journal

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== External links ==

* [http://www.inductive-programming.org/ Inductive Programming community page], hosted by the University of Bamberg.

{{Programming paradigms navbox}}

[[Category:Programming paradigms]]