Repair theory

A generative theory of bugs in procedural skills

John Seely Brown, Kurt VanLehn

Research output: Contribution to journalArticle

Abstract

This paper describes a generative theory of bugs. It claims that all bugs of a procedural skill can be derived by a highly constrained form of problem solving acting on incomplete procedures. These procedures are characterized by formal deletion operations that model incomplete learning and forgetting. The problem solver and the deletion operator have been constrained to make it impossible to derive “star-bugs”—algorithms that are so absurd that expert diagnosticians agree that the alogorithm will never be observed as a bug. Hence, the theory not only generates the observed bugs, it fails to generate star-bugs. The theory has been tested on an extensive data base of bugs for multidigit subtraction that was collected with the aid of the diagnostic systems buggy and debuggy. In addition to predicting bug occurrence, by adoption of additional hypotheses, the theory also makes predictions about the frequency and stability of bugs, as well as the occurrence of certain latencies in processing time during testing. Arguments are given that the theory can be applied to domains other than subtraction and that it can be extended to provide a theory of procedural learning that accounts for bug acquisition. Lastly, particular care has been taken to make the theory principled so that it can not be tailored to fit any possible data.

Original languageEnglish (US)
Pages (from-to)379-426
Number of pages48
JournalCognitive Science
Volume4
Issue number4
DOIs
StatePublished - 1980
Externally publishedYes

Fingerprint

Stars
Repair
Learning
Databases
Testing
Processing
Procedural
Theodore Roszak
Generative

ASJC Scopus subject areas

  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence

Cite this

Repair theory : A generative theory of bugs in procedural skills. / Brown, John Seely; VanLehn, Kurt.

In: Cognitive Science, Vol. 4, No. 4, 1980, p. 379-426.

Research output: Contribution to journalArticle

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