Encyclopedia of Machine Learning

2010 Edition
| Editors: Claude Sammut, Geoffrey I. Webb

Trace-Based Programming

  • Pierre Flener
  • Ute Schmid
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-30164-8_838



Trace-based programming addresses the inference of a program from a small set of example computation traces. The induced program is typically a recursive program. A computation trace is a nonrecursive expression that describes the transformation of some specific input into the desired output with help of a predefined set of primitive functions. While the construction of traces is highly dependent on background knowledge or even on knowledge about the program searched for, the inductive  generalization is based on syntactical methods of detecting regularities and dependencies between traces, as proposed in classical approaches to  inductive programming (see Example 5 of that encyclopedia entry) or  explanation-based learning (EBL). As an alternative to providing traces by hand-simulation, AI planning techniques or  programming by demonstration (PBD) can be used.

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© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Pierre Flener
  • Ute Schmid

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