{"id":"https://openalex.org/W2555070104","doi":"https://doi.org/10.1109/hldvt.2016.7748265","title":"Estimation of formal verification cost using regression machine learning","display_name":"Estimation of formal verification cost using regression machine learning","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2555070104","doi":"https://doi.org/10.1109/hldvt.2016.7748265","mag":"2555070104"},"language":"en","primary_location":{"id":"doi:10.1109/hldvt.2016.7748265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hldvt.2016.7748265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International High Level Design Validation and Test Workshop (HLDVT)","raw_type":"proceedings-article"},"type":"article","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/A5001510113","display_name":"Eman El Mandouh","orcid":null},"institutions":[{"id":"https://openalex.org/I105695857","display_name":"Siemens (Hungary)","ror":"https://ror.org/01rk7mv85","country_code":"HU","type":"company","lineage":["https://openalex.org/I105695857","https://openalex.org/I1325886976"]},{"id":"https://openalex.org/I4210099704","display_name":"Mentor","ror":"https://ror.org/016grqh48","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210099704"]}],"countries":["GB","HU"],"is_corresponding":true,"raw_author_name":"Eman El Mandouh","raw_affiliation_strings":["Mentor Graphics Corporation Design Verification Technology"],"affiliations":[{"raw_affiliation_string":"Mentor Graphics Corporation Design Verification Technology","institution_ids":["https://openalex.org/I105695857","https://openalex.org/I4210099704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049534161","display_name":"Amr G. Wassal","orcid":"https://orcid.org/0000-0001-6009-4174"},"institutions":[{"id":"https://openalex.org/I145487455","display_name":"Cairo University","ror":"https://ror.org/03q21mh05","country_code":"EG","type":"education","lineage":["https://openalex.org/I145487455"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Amr G. Wassal","raw_affiliation_strings":["Computer Engineering Department Cairo University, Egypt"],"affiliations":[{"raw_affiliation_string":"Computer Engineering Department Cairo University, Egypt","institution_ids":["https://openalex.org/I145487455"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001510113"],"corresponding_institution_ids":["https://openalex.org/I105695857","https://openalex.org/I4210099704"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.1331578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"73","issue":null,"first_page":"121","last_page":"127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.7561842203140259},{"id":"https://openalex.org/keywords/formal-verification","display_name":"Formal verification","score":0.6942490339279175},{"id":"https://openalex.org/keywords/formal-methods","display_name":"Formal methods","score":0.6438217163085938},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48005518317222595},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.44601088762283325},{"id":"https://openalex.org/keywords/formal-proof","display_name":"Formal proof","score":0.43800613284111023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4238676428794861},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4190983176231384},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.41523993015289307},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4146113395690918},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28814950585365295},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14310884475708008},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12409454584121704},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.11487126350402832},{"id":"https://openalex.org/keywords/mathematical-proof","display_name":"Mathematical proof","score":0.09716334939002991}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7561842203140259},{"id":"https://openalex.org/C111498074","wikidata":"https://www.wikidata.org/wiki/Q173326","display_name":"Formal verification","level":2,"score":0.6942490339279175},{"id":"https://openalex.org/C75606506","wikidata":"https://www.wikidata.org/wiki/Q1049183","display_name":"Formal methods","level":2,"score":0.6438217163085938},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48005518317222595},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.44601088762283325},{"id":"https://openalex.org/C94461902","wikidata":"https://www.wikidata.org/wiki/Q2762418","display_name":"Formal proof","level":3,"score":0.43800613284111023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4238676428794861},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4190983176231384},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.41523993015289307},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4146113395690918},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28814950585365295},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14310884475708008},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12409454584121704},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.11487126350402832},{"id":"https://openalex.org/C108710211","wikidata":"https://www.wikidata.org/wiki/Q11538","display_name":"Mathematical proof","level":2,"score":0.09716334939002991},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hldvt.2016.7748265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hldvt.2016.7748265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International High Level Design Validation and Test Workshop (HLDVT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1709433961","https://openalex.org/W1836910194","https://openalex.org/W1976597924","https://openalex.org/W1981552604","https://openalex.org/W1985258161","https://openalex.org/W2013145190","https://openalex.org/W2020239492","https://openalex.org/W2043478128","https://openalex.org/W2050033680","https://openalex.org/W2113539181","https://openalex.org/W2135046866","https://openalex.org/W2181650752","https://openalex.org/W2207993524","https://openalex.org/W2797532987","https://openalex.org/W3104887532","https://openalex.org/W3105543546","https://openalex.org/W3148030813","https://openalex.org/W4230236249","https://openalex.org/W4238530616","https://openalex.org/W4248877409","https://openalex.org/W6644480423","https://openalex.org/W6680156768","https://openalex.org/W6687955017"],"related_works":["https://openalex.org/W161255303","https://openalex.org/W1544097700","https://openalex.org/W31220157","https://openalex.org/W1488573418","https://openalex.org/W2152752131","https://openalex.org/W1922520186","https://openalex.org/W1946493810","https://openalex.org/W2391979747","https://openalex.org/W1495250406","https://openalex.org/W2293611133"],"abstract_inverted_index":{"Formal":[0],"Verification":[1],"is":[2,178],"a":[3,43,160],"computationally":[4],"expensive":[5],"step":[6,146],"in":[7,124],"the":[8,26,38,54,60,76,90,114,120,132,139,143,150,155,163,183,190,200],"verification":[9,99,203],"of":[10,45,59,78,92,107,126,134,152],"today's":[11],"complex":[12],"hardware":[13],"designs.":[14,208],"Effective":[15],"results":[16,187],"can":[17],"be":[18],"obtained":[19],"from":[20],"formal":[21,61,93,98,122,127,202],"runs":[22,100],"by":[23],"planning":[24],"ahead":[25],"effort":[27,204],"and":[28,48,63,119,169],"cost":[29,91,123],"that":[30],"are":[31,110],"required":[32],"for":[33,89,154,205],"them.":[34],"Additionally":[35],"estimating":[36],"in-advance":[37],"expected":[39,201],"formal's":[40],"complexity":[41],"promotes":[42],"lot":[44],"potential":[46],"tricks":[47],"clever":[49],"setup":[50],"techniques":[51,83],"to":[52,67,84,96,112,136,180,194],"overcome":[53],"initial":[55],"push-button":[56],"capacity":[57],"limitation":[58],"verifies":[62],"improve":[64],"their":[65],"capabilities":[66],"handle":[68],"designs":[69,103,118],"with":[70,104,196],"higher":[71],"complexity.":[72],"This":[73],"paper":[74],"illustrates":[75],"application":[77,151],"regression":[79,167,176],"machine":[80],"learning":[81],"(ML)":[82],"build":[85],"an":[86],"estimation":[87],"model":[88,192],"verification.":[94],"Up":[95],"10,000":[97],"on":[101,138,182],"RTL":[102],"good":[105],"varieties":[106],"design/properties":[108],"attributes":[109],"used":[111],"learn":[113],"relationship":[115],"between":[116,162],"HW":[117,207],"final":[121],"terms":[125],"run":[128],"time.":[129],"We":[130],"demonstrate":[131],"use":[133],"Ridge-Regression":[135],"decide":[137],"bias-variance":[140],"trade-off":[141],"during":[142],"regression-model":[144],"design":[145],"as":[147,149],"well":[148],"Lasso-Regression":[153],"feature":[156],"selection":[157],"phase.":[158],"Finally":[159],"comparison":[161],"proposed":[164,191],"multiple":[165],"linear":[166],"approach":[168],"another":[170],"non-parametric":[171],"K-nearest":[172],"neighbors":[173],"kernel":[174],"based":[175],"technique":[177],"done":[179],"conclude":[181],"presented":[184],"work.":[185],"Our":[186],"indicate":[188],"how":[189],"managed":[193],"estimate":[195],"reasonable":[197],"error":[198],"ratio":[199],"new-to-verify":[206]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
