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Rippling: Meta-Level Guidance for Mathematical Reasoning
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  • Cited by 6
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    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Bundy, Alan Cavallo, Flaminia Dixon, Lucas Johansson, Moa and McCasland, Roy 2015. The Theory behind Theory Mine. IEEE Intelligent Systems, Vol. 30, Issue. 4, p. 64.

    Eberhard, Sebastian and Hetzl, Stefan 2015. Inductive theorem proving based on tree grammars. Annals of Pure and Applied Logic, Vol. 166, Issue. 6, p. 665.

    Grov, Gudmund Kissinger, Aleks and Lin, Yuhui 2014. Tinker, tailor, solver, proof. Electronic Proceedings in Theoretical Computer Science, Vol. 167, p. 23.

    Dennis, Louise Abigail Green, Ian and Smaill, Alan 2011. The Use of Embeddings to Provide a Clean Separation of Term and Annotation for Higher Order Rippling. Journal of Automated Reasoning, Vol. 47, Issue. 1, p. 57.

    Dramnesc, Isabela and Jebelean, Tudor 2011. 2011 13th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. p. 101.

    Ireland, Andrew 2006. 21st IEEE/ACM International Conference on Automated Software Engineering (ASE'06). p. 309.

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    Rippling: Meta-Level Guidance for Mathematical Reasoning
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Book description

Rippling is a radically new technique for the automation of mathematical reasoning. It is widely applicable whenever a goal is to be proved from one or more syntactically similar givens. It was originally developed for inductive proofs, where the goal was the induction conclusion and the givens were the induction hypotheses. It has proved to be applicable to a much wider class of tasks, from summing series via analysis to general equational reasoning. The application to induction has especially important practical implications in the building of dependable IT systems, and provides solutions to issues such as the problem of combinatorial explosion. Rippling is the first of many new search control techniques based on formula annotation; some additional annotated reasoning techniques are also described here. This systematic and comprehensive introduction to rippling, and to the wider subject of automated inductive theorem proving, will be welcomed by researchers and graduate students alike.

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