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Inductive Synthesis of Recursive Functional Programs
A Comparison of Three Systems

Martin HofmannContact Information, Andreas HirschbergerContact Information, Emanuel KitzelmannnContact Information and Ute SchmidContact Information

(1)  University of Bamberg, Faculty of Information Systems, and Applied Computer Science,  
Abstract
One of the most challenging subfields, and a still little researched niche of machine learning, is the inductive synthesis of recursive programs from incomplete specifications, such as examples for the desired input/output behavior [1,2,3,4].

Contact Information Martin Hofmann
Email: martin.hofmann@stud.uni-bamberg.de

Contact Information Andreas Hirschberger
Email: andreas.hirschberger@stud.uni-bamberg.de

Contact Information Emanuel Kitzelmannn
Email: emanuel.kitzelmann@wiai.uni-bamberg.de

Contact Information Ute Schmid
Email: ute.schmid@wiai.uni-bamberg.de
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