Polynomial-time inverse computation for accumulative functions with multiple data traversals

  • Authors:

  • Kazutaka Matsuda;Kazuhiro Inaba;Keisuke Nakano

  • Affiliations:

  • Tohoku University, Sendai, Japan;National Institute of Informatics , Tokyo, Japan;The University of Electro-Communications, Tokyo, Japan

  • Venue:
  • PEPM '12 Proceedings of the ACM SIGPLAN 2012 workshop on Partial evaluation and program manipulation
  • Year:
  • 2012

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Abstract

Inverse computation has many applications such as serialization/deserialization, providing support for undo, and test-case generation for software testing. In this paper, we propose an inverse computation method that always terminates for a class of functions known as parameter-linear macro tree transducers, which involve multiple data traversals and the use of accumulations. The key to our method is the observation that a function in the class can be regarded as a non-accumulative context-generating transformation without multiple data traversals. Accordingly, we demonstrate that it is easy to achieve terminating inverse computation for the class by context-wise memoization of the inverse computation results. We also show that when we use a tree automaton to express the inverse computation results, the inverse computation runs in time polynomial to the size of the original output and the textual program size.