{"id":"https://openalex.org/W4312081888","doi":"https://doi.org/10.1109/ats56056.2022.00034","title":"Hybrid Rule-based and Machine Learning System for Assertion Generation from Natural Language Specifications","display_name":"Hybrid Rule-based and Machine Learning System for Assertion Generation from Natural Language Specifications","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4312081888","doi":"https://doi.org/10.1109/ats56056.2022.00034"},"language":"en","primary_location":{"id":"doi:10.1109/ats56056.2022.00034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ats56056.2022.00034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 31st Asian Test Symposium (ATS)","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/A5009577705","display_name":"Fnu Aditi","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fnu Aditi","raw_affiliation_strings":["Virginia Tech Blacksburg,Department of Electrical and Computer Engineering,Virginia,USA,24061"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech Blacksburg,Department of Electrical and Computer Engineering,Virginia,USA,24061","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108516165","display_name":"Michael S. Hsiao","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael S. Hsiao","raw_affiliation_strings":["Virginia Tech Blacksburg,Department of Electrical and Computer Engineering,Virginia,USA,24061"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech Blacksburg,Department of Electrical and Computer Engineering,Virginia,USA,24061","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"126","last_page":"131"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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/T10260","display_name":"Software Engineering Research","score":0.9970999956130981,"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/T10028","display_name":"Topic Modeling","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8486312627792358},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7007564306259155},{"id":"https://openalex.org/keywords/assertion","display_name":"Assertion","score":0.6224470138549805},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.6158737540245056},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.5966601371765137},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.5588436126708984},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.5551472306251526},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5085722208023071},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.420763224363327}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8486312627792358},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7007564306259155},{"id":"https://openalex.org/C40422974","wikidata":"https://www.wikidata.org/wiki/Q741248","display_name":"Assertion","level":2,"score":0.6224470138549805},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.6158737540245056},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5966601371765137},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.5588436126708984},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.5551472306251526},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5085722208023071},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.420763224363327}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ats56056.2022.00034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ats56056.2022.00034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 31st Asian Test Symposium (ATS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G5152983834","display_name":"SHF CORE: Small: Hybrid NLP and Formal Techniques for Synthesizing Assertions and Identifying Ambiguities from English","funder_award_id":"2101021","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2345350761","https://openalex.org/W2921499078","https://openalex.org/W2946741689","https://openalex.org/W2973193739","https://openalex.org/W2981952055","https://openalex.org/W3082750925","https://openalex.org/W3177813494","https://openalex.org/W4292779060","https://openalex.org/W6778883912","https://openalex.org/W6782380205","https://openalex.org/W6798182279"],"related_works":["https://openalex.org/W1498103021","https://openalex.org/W2035655557","https://openalex.org/W4230849338","https://openalex.org/W4295166216","https://openalex.org/W2177044681","https://openalex.org/W1968067090","https://openalex.org/W2090313512","https://openalex.org/W2345942070","https://openalex.org/W2293063786","https://openalex.org/W2911292476"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,51,57,81],"hybrid":[3,52,78,105],"approach":[4,79],"for":[5,70],"automatic":[6],"generation":[7],"of":[8,21,56,93,103],"System":[9],"Verilog":[10],"assertions":[11,87],"from":[12],"natural-language":[13],"specifications":[14],"by":[15],"combining":[16],"machine-learning":[17,59,95],"and":[18,62],"formal":[19,26,46],"analysis":[20,27],"the":[22,31,35,42,54,66,76,86,91,101,104],"input":[23,32,43],"text.":[24],"The":[25],"focuses":[28,39],"on":[29,40],"parsing":[30],"text,":[33],"while":[34],"machine":[36],"learning":[37],"engine":[38],"translating":[41],"text":[44],"to":[45,84,99],"logic":[47],"and/or":[48],"assertions.":[49,73],"Such":[50],"reduces":[53],"burden":[55],"purely":[58],"based":[60],"translation":[61],"increases":[63],"accuracy":[64],"in":[65,89],"generated":[67],"assertions,":[68],"especially":[69],"those":[71],"complex":[72],"In":[74],"addition,":[75],"proposed":[77],"offers":[80],"novel":[82],"method":[83],"validate":[85],"generated,":[88],"which":[90],"results":[92],"different":[94],"models":[96],"are":[97],"used":[98],"determine":[100],"confidence":[102],"approach.":[106]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}