Some models of inductive syntactical synthesis from sample computations

Abstract

The paper is a survey of several models of inductive program synthesis from sample computations. Synthesis tools are basically syntactical: the synthesis is based on the detection of "regular" fragments related with "shuffled" arithmetical progressions. Input sample computations are supposed to be "representative": they have to "reflect" all loops occurring in the target program. Programs are synthesized in nontraditional form of "generalized" regular expressions having Cleene stars and unions for loops and CASE-like operators. However, if input samples are somehow "annotated" (we consider two different approaches), then loops can be synthesized in more traditional WHILE-form, where loop conditions are separated from actions. The model in Section 3 is developed to handle the synthesis from incomplete sample computations (initial fragments). This model can be useful for the synthesis of some divide-and-conquer algorithms.