{"id":"https://openalex.org/W2588459340","doi":"https://doi.org/10.1109/aspdac.2017.7858295","title":"Feature extraction from design documents to enable rule learning for improving assertion coverage","display_name":"Feature extraction from design documents to enable rule learning for improving assertion coverage","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2588459340","doi":"https://doi.org/10.1109/aspdac.2017.7858295","mag":"2588459340"},"language":"en","primary_location":{"id":"doi:10.1109/aspdac.2017.7858295","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aspdac.2017.7858295","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034427067","display_name":"Kuo-Kai Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kuo-Kai Hsieh","raw_affiliation_strings":["University of California, Santa Barbara"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001012837","display_name":"Sebastian Siatkowski","orcid":null},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sebastian Siatkowski","raw_affiliation_strings":["University of California, Santa Barbara"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100369642","display_name":"Li-C. Wang","orcid":"https://orcid.org/0000-0003-4851-8004"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li-C. Wang","raw_affiliation_strings":["University of California, Santa Barbara"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085836910","display_name":"Wen Chen","orcid":"https://orcid.org/0000-0002-3258-7278"},"institutions":[{"id":"https://openalex.org/I4210123704","display_name":"NXP (Germany)","ror":"https://ror.org/0268h4j55","country_code":"DE","type":"company","lineage":["https://openalex.org/I109147379","https://openalex.org/I4210123704"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wen Chen","raw_affiliation_strings":["NXP Semiconductors, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NXP Semiconductors, Inc","institution_ids":["https://openalex.org/I4210123704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108510816","display_name":"Jayanta Bhadra","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123704","display_name":"NXP (Germany)","ror":"https://ror.org/0268h4j55","country_code":"DE","type":"company","lineage":["https://openalex.org/I109147379","https://openalex.org/I4210123704"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jayanta Bhadra","raw_affiliation_strings":["NXP Semiconductors, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NXP Semiconductors, Inc","institution_ids":["https://openalex.org/I4210123704"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"51","last_page":"56"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10142","display_name":"Formal Methods in Verification","score":0.9722999930381775,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8166462182998657},{"id":"https://openalex.org/keywords/assertion","display_name":"Assertion","score":0.6911762356758118},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5761295557022095},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5237022638320923},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5236682295799255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5189166069030762},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5025687217712402},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4891972541809082},{"id":"https://openalex.org/keywords/rule-based-system","display_name":"Rule-based system","score":0.48417359590530396},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48357290029525757},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4685196578502655},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.44801682233810425},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.41131591796875},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3718015253543854},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3221879005432129},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.12571126222610474}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8166462182998657},{"id":"https://openalex.org/C40422974","wikidata":"https://www.wikidata.org/wiki/Q741248","display_name":"Assertion","level":2,"score":0.6911762356758118},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5761295557022095},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5237022638320923},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5236682295799255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5189166069030762},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5025687217712402},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4891972541809082},{"id":"https://openalex.org/C149271511","wikidata":"https://www.wikidata.org/wiki/Q1417149","display_name":"Rule-based system","level":2,"score":0.48417359590530396},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48357290029525757},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4685196578502655},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.44801682233810425},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.41131591796875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3718015253543854},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3221879005432129},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.12571126222610474},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aspdac.2017.7858295","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aspdac.2017.7858295","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1594031697","https://openalex.org/W1974291029","https://openalex.org/W2018560257","https://openalex.org/W2081687495","https://openalex.org/W2101234009","https://openalex.org/W2113340410","https://openalex.org/W2117874980","https://openalex.org/W2120263045","https://openalex.org/W2135843243","https://openalex.org/W2136000097","https://openalex.org/W2141261568","https://openalex.org/W2143017621","https://openalex.org/W2168238416","https://openalex.org/W2998617017","https://openalex.org/W3142765463","https://openalex.org/W4234760406","https://openalex.org/W4243200998","https://openalex.org/W4250788613","https://openalex.org/W4251372957","https://openalex.org/W6675354045","https://openalex.org/W6678091135"],"related_works":["https://openalex.org/W1498103021","https://openalex.org/W4230849338","https://openalex.org/W4295166216","https://openalex.org/W2177044681","https://openalex.org/W1968067090","https://openalex.org/W2345942070","https://openalex.org/W2141398161","https://openalex.org/W2016410697","https://openalex.org/W39611005","https://openalex.org/W653076280"],"abstract_inverted_index":{"Feature":[0],"selection":[1,22],"is":[2],"essential":[3],"to":[4,42,54],"rule":[5,44],"learning":[6],"in":[7],"the":[8,21,56,82],"context":[9],"of":[10,62,81],"functional":[11],"verification.":[12],"In":[13,26],"practice":[14],"today,":[15],"features":[16,51],"are":[17,52],"selected":[18],"manually":[19],"and":[20],"requires":[23],"domain":[24],"knowledge.":[25],"contrast,":[27],"this":[28],"work":[29],"proposes":[30],"using":[31],"automatic":[32],"feature":[33],"extraction":[34],"from":[35],"design":[36],"documents":[37],"as":[38],"a":[39,60,66],"viable":[40],"approach":[41],"support":[43],"learning.":[45],"To":[46],"demonstrate":[47],"its":[48],"effectiveness,":[49],"document-extracted":[50],"employed":[53],"learn":[55],"rules":[57,73],"for":[58,77],"covering":[59],"set":[61],"assertions":[63],"based":[64],"on":[65],"commercial":[67],"SoC.":[68],"Experiments":[69],"show":[70],"that":[71],"100%-accurate":[72],"can":[74],"be":[75],"obtained":[76],"more":[78],"than":[79],"70%":[80],"assertions.":[83]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}