Inferring Flow of Control in Program Synthesis by Example

  • Authors:
  • Stefan Schrödl;Stefan Edelkamp

  • Affiliations:
  • -;-

  • Venue:
  • KI '99 Proceedings of the 23rd Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
  • Year:
  • 1999

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Abstract

We present a supervised, interactive learning technique that infers control structures of computer programs from user-demonstrated traces. A two-stage process is applied: first, a minimal deterministic finite automaton (DFA) M labeled by the instructions of the program is learned from a set of example traces and membership queries to the user. It accepts all prefixes of traces of the target program. The number of queries is bounded by O(k ˙ |M|), with k being the total number of instructions in the initial example traces. In the second step we parse this automaton into a high-level programming language in O(|M|2) steps, replacing jumps by conditional control structures.