Synthesis of UNIX Programs using Derivational Analogy

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Citation: Sanjay Bhansali and Mehdi T. Harandi. (1992) Synthesis of UNIX Programs using Derivational Analogy. In KSL-92-02, 1992.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Sanjay Bhansali and Mehdi T. Harandi
title Synthesis of UNIX Programs using Derivational Analogy
number KSL-92-02
institution Knowledge Systems, AI Laboratory
year 1992
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abstract The feasibility of derivational analogy as a mechanism for improving problem-solving behavior has been shown for a variety of problem domains by several researchers. However, most of the implemented systems have been empirically evaluated in the restricted context of an already supplied base analog, or on a few isolated examples. In this paper we describe a derivational analogy based system, APU, that sythesizes UNIX shell scripts from a high-level problem specification. APU uses top down decomposition of problems, employing a hierarchical planner and a layered knowledge base of rules, and is able to speed up the derivation of programs by using derivational analogy. We assume that the problem specification is encoded in the vocabulary used by the rules. We describe APU's retrieval heuristics that exploit this assumption to automatically retrieve a good analog for a target problem from a case library, as well as its replay algorithm that enables it to effectively reuse the solution of an analogous problem to derive a solution for a new problem. We present experimental results to assess APU's performance, taking into account the cost of retrieving analogs form a sizable case library. We discuss the significance of the results and some of the issues in using derivational analogy to synthesize programs.

KSL Technical Report ID: KSL-92-02
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Abstract The feasibility of derivational analogy as … The feasibility of derivational analogy as a mechanism for improving problem-solving behavior has been shown for a variety of problem domains by several researchers. However, most of the implemented systems have been empirically evaluated in the restricted context of an already supplied base analog, or on a few isolated examples. In this paper we describe a derivational analogy based system, APU, that sythesizes UNIX shell scripts from a high-level problem specification. APU uses top down decomposition of problems, employing a hierarchical planner and a layered knowledge base of rules, and is able to speed up the derivation of programs by using derivational analogy. We assume that the problem specification is encoded in the vocabulary used by the rules. We describe APU's retrieval heuristics that exploit this assumption to automatically retrieve a good analog for a target problem from a case library, as well as its replay algorithm that enables it to effectively reuse the solution of an analogous problem to derive a solution for a new problem. We present experimental results to assess APU's performance, taking into account the cost of retrieving analogs form a sizable case library. We discuss the significance of the results and some of the issues in using derivational analogy to synthesize programs. rivational analogy to synthesize programs.
Author Sanjay Bhansali and Mehdi T. Harandi  +
Bibtype techreport  +
Has author Sanjay Bhansali and Mehdi T. Harandi  +
Has identifier KSL-92-02  +
Has publishing details 1992  +
Has title Synthesis of UNIX Programs using Derivational Analogy  +
Has where published KSL-92-02  +
Has year 1992  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-92-02  +
Number KSL-92-02  +
Process note YES  +
Title Synthesis of UNIX Programs using Derivational Analogy  +
Year 1992  +
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