• DocumentCode
    1786755
  • Title

    Ontology-guided conceptual analysis of design specifications

  • Author

    Shankar, Ashwin ; Singh, Bawa ; Wolff, Francis ; Papachristou, C.

  • Author_Institution
    Case Western Reserve Univ., Cleveland, OH, USA
  • fYear
    2014
  • fDate
    1-5 June 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The integration of reusable IP blocks/cores is a common process in system-on-chip design and involves manually comparing/mapping IP specifications against system requirements. The informal nature of specification limits its automatic analysis. Existing techniques fail to utilize the underlying conceptual information embedded in specifications. In this paper, we present a methodology for specification analysis, which involves concept mining of specifications to generate domain ontologies. We employ a semi-supervised expert system with semantic analysis capability to create a collaborative framework for cumulative knowledge acquisition. Our system then uses the generated ontologies to perform component retrieval, drop-in-replacement analysis and design vs. test-plan comparisons. We demonstrate our approach by evaluating several IP specifications.
  • Keywords
    data mining; expert systems; information retrieval; logic design; ontologies (artificial intelligence); system-on-chip; IP specification comparison; IP specification mapping; Internet protocol; component retrieval; concept mining; conceptual information; cumulative knowledge acquisition; design specifications; domain ontologies; drop-in-replacement analysis; ontology-guided conceptual analysis; reusable IP blocks; reusable IP cores; semi-supervised expert system; specification analysis; system-on-chip design; Algorithm design and analysis; Data mining; IP networks; Indexes; Inspection; Ontologies; Semantics; Component Retrieval; Conceptual Analysis; Ontology; Ontology Generation; Semantic Web; Specification Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design Automation Conference (DAC), 2014 51st ACM/EDAC/IEEE
  • Conference_Location
    San Francisco, CA
  • Type

    conf

  • DOI
    10.1145/2593069.2593175
  • Filename
    6881361