Automated Support for Diagnosis and Repair.

The article discusses the use of model checking and artificial intelligence in diagnosing and repairing problems in the software development cycle. The authors describe a four-step framework for a basic train-controller system that includes model checking, elicitation by the software engineer of sys...

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Publicado en:Communications of the ACM Vol. 58; no. 2; pp. 65 - 73
Autores principales: ALRAJEH, DALAL, KRAMER, JEFF, RUSSO, ALESSANDRA, UCHITEL, SEBASTIAN
Formato: Artículo
Publicado: Association for Computing Machinery Feb2015
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          ALRAJEH, DALAL
          KRAMER, JEFF
          RUSSO, ALESSANDRA
          UCHITEL, SEBASTIAN
        affil:
          Junior research fellow, Department of Computing, Imperial College London, U.K.
          Professor of distributed computing, Department of Computing, Imperial College London, U.K.
          Reader in applied computational logic, Department of Computing, Imperial College London, U.K.
          Reader in software engineering, Department of Computing, Imperial College London, U.K.
          Ad-honorem professor, Departamento de Computation and the National Scientific and Technical Research Council, or CONICET,University of Buenos Aires, Argentina
      su:
        Computer software quality control
        Software engineering
        Computer software development
        Artificial intelligence
        Logic machines
        Machine learning
      sug:
        subj:
          Computer software quality control
          Software engineering
          Computer software development
          Artificial intelligence
          Logic machines
          Machine learning
      ab: The article discusses the use of model checking and artificial intelligence in diagnosing and repairing problems in the software development cycle. The authors describe a four-step framework for a basic train-controller system that includes model checking, elicitation by the software engineer of system states that address inconsistencies in counterexamples produced by the model checking, repair of defective states by logic-based learning, and implementation of a selection mechanism to choose among alternative approaches to the same repair task.
      pubtype: Periodical
      doctype: Article
      src: R
    language: English
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