Titlebook: Logic Program Synthesis from Incomplete Information; Pierre Flener Book 1995 Springer Science+Business Media Dordrecht 1995 algorithms.art

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Inductive Inference in Automatic Programminges. In Section 3.2, we present the major results about inductive inference. Then, in Section 3.3 and Section 3.4, we survey the synthesis of functional programs from examples, and the synthesis of logic programs from examples, respectively. Finally, in Section 3.5, we draw some conclusions on the us

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A Logic Program Development Methodologynt, we summarize that methodology, and put special focus on aspects directly related to our research. This summary mainly states results, and not always their motivations or proofs: refer to [Deville 90] when in need of further explanations.

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A Specification Approachere to investigate synthesis from incomplete specifications. Starting from the pros and cons of specifi- cations by examples, and of specifications by axioms, as outlined in Part I, we define, in Section 6.1, a specification approach that is based on examples and properties. Then, in Section 6.2, we

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Algorithm Analysis and Algorithm Schemataing algorithm design. Then, in Section 8.2, we introduce a logic algorithm schema reflecting a divide-and-conquer design strategy. This allows us, in Section 8.3, to refine the framework of Chapter 7 to stepwise and schema-guided synthesis of logic algorithms from examples and properties. Future wor

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The Proofs-as-Programs Methodties become satisfied. This method is part of our tool-box of methods for instantiating the predicate- variables of a schema. First, in Section 9.1, we state the problem. Then, in Section 9.2, we explain a method to solve this problem, and discuss its correctness in Section 9.3. In Section 9.4, we i

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The Most-Specific-Generalization Methodom examples. This method is part of our tool-box of methods for instantiating the predicate-variables of a schema. First, in Section 10.1, we define the concept of most-specific- generalization. Then, in Section 10.2, we state the objective of the MSG Method, and introduce some other preliminary ter