{"id":"https://openalex.org/W4303833109","doi":"https://doi.org/10.3390/make4040045","title":"How Do Deep-Learning Framework Versions Affect the Reproducibility of Neural Network Models?","display_name":"How Do Deep-Learning Framework Versions Affect the Reproducibility of Neural Network Models?","publication_year":2022,"publication_date":"2022-10-05","ids":{"openalex":"https://openalex.org/W4303833109","doi":"https://doi.org/10.3390/make4040045"},"language":"en","primary_location":{"id":"doi:10.3390/make4040045","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make4040045","pdf_url":"https://www.mdpi.com/2504-4990/4/4/45/pdf?version=1665735645","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/4/4/45/pdf?version=1665735645","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026876282","display_name":"Mostafa Shahriari","orcid":"https://orcid.org/0000-0002-2881-1177"},"institutions":[{"id":"https://openalex.org/I4210126338","display_name":"Software Competence Center Hagenberg (Austria)","ror":"https://ror.org/02ks3nr96","country_code":"AT","type":"company","lineage":["https://openalex.org/I4210126338"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Mostafa Shahriari","raw_affiliation_strings":["Software Competence Center Hagenberg GmbH (SCCH), 4232 Hagenberg, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Software Competence Center Hagenberg GmbH (SCCH), 4232 Hagenberg, Austria","institution_ids":["https://openalex.org/I4210126338"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004548330","display_name":"Rudolf Ramler","orcid":"https://orcid.org/0000-0001-9903-6107"},"institutions":[{"id":"https://openalex.org/I4210126338","display_name":"Software Competence Center Hagenberg (Austria)","ror":"https://ror.org/02ks3nr96","country_code":"AT","type":"company","lineage":["https://openalex.org/I4210126338"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Rudolf Ramler","raw_affiliation_strings":["Software Competence Center Hagenberg GmbH (SCCH), 4232 Hagenberg, Austria"],"raw_orcid":"https://orcid.org/0000-0001-9903-6107","affiliations":[{"raw_affiliation_string":"Software Competence Center Hagenberg GmbH (SCCH), 4232 Hagenberg, Austria","institution_ids":["https://openalex.org/I4210126338"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009274955","display_name":"Lukas Fischer","orcid":"https://orcid.org/0000-0001-5303-6638"},"institutions":[{"id":"https://openalex.org/I4210126338","display_name":"Software Competence Center Hagenberg (Austria)","ror":"https://ror.org/02ks3nr96","country_code":"AT","type":"company","lineage":["https://openalex.org/I4210126338"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Lukas Fischer","raw_affiliation_strings":["Software Competence Center Hagenberg GmbH (SCCH), 4232 Hagenberg, Austria"],"raw_orcid":"https://orcid.org/0000-0001-5303-6638","affiliations":[{"raw_affiliation_string":"Software Competence Center Hagenberg GmbH (SCCH), 4232 Hagenberg, Austria","institution_ids":["https://openalex.org/I4210126338"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5026876282"],"corresponding_institution_ids":["https://openalex.org/I4210126338"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.9275,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.78370735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"4","issue":"4","first_page":"888","last_page":"911"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9973000288009644,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9973000288009644,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9969000220298767,"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":0.9965999722480774,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/debugging","display_name":"Debugging","score":0.8124587535858154},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8123334646224976},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6206427216529846},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5791947245597839},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.577877402305603},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5761314630508423},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.5370236039161682},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5345261693000793},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5304044485092163},{"id":"https://openalex.org/keywords/software-bug","display_name":"Software bug","score":0.4913841784000397},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.48172929883003235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4762459099292755},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.46913856267929077},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4113166332244873},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.13913747668266296}],"concepts":[{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.8124587535858154},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8123334646224976},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6206427216529846},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5791947245597839},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.577877402305603},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5761314630508423},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.5370236039161682},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5345261693000793},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5304044485092163},{"id":"https://openalex.org/C1009929","wikidata":"https://www.wikidata.org/wiki/Q179550","display_name":"Software bug","level":3,"score":0.4913841784000397},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.48172929883003235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4762459099292755},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.46913856267929077},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4113166332244873},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.13913747668266296},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/make4040045","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make4040045","pdf_url":"https://www.mdpi.com/2504-4990/4/4/45/pdf?version=1665735645","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5cbc7d5a52604dc082f33116c35cdef7","is_oa":true,"landing_page_url":"https://doaj.org/article/5cbc7d5a52604dc082f33116c35cdef7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 4, Iss 4, Pp 888-911 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2504-4990/4/4/45/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/make4040045","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction; Volume 4; Issue 4; Pages: 888-911","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/make4040045","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make4040045","pdf_url":"https://www.mdpi.com/2504-4990/4/4/45/pdf?version=1665735645","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.6000000238418579,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4303833109.pdf"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1968691112","https://openalex.org/W2148143831","https://openalex.org/W2741881058","https://openalex.org/W2774185825","https://openalex.org/W2788572835","https://openalex.org/W2799424953","https://openalex.org/W2850992922","https://openalex.org/W2859484040","https://openalex.org/W2890056718","https://openalex.org/W2922234936","https://openalex.org/W2943179835","https://openalex.org/W2963459284","https://openalex.org/W2968594320","https://openalex.org/W2970971581","https://openalex.org/W2997681568","https://openalex.org/W3008058947","https://openalex.org/W3010868305","https://openalex.org/W3045230952","https://openalex.org/W3090643686","https://openalex.org/W3092775028","https://openalex.org/W3107770003","https://openalex.org/W3110285703","https://openalex.org/W3117442988","https://openalex.org/W3122184684","https://openalex.org/W3149582851","https://openalex.org/W3173813052","https://openalex.org/W3176115515","https://openalex.org/W3177349994","https://openalex.org/W3183977027","https://openalex.org/W3196967454","https://openalex.org/W3214379748","https://openalex.org/W4200064178","https://openalex.org/W4312809370","https://openalex.org/W4317761959","https://openalex.org/W4362606928","https://openalex.org/W6748072260","https://openalex.org/W6754343823","https://openalex.org/W6797386277","https://openalex.org/W6803494062"],"related_works":["https://openalex.org/W2740264376","https://openalex.org/W4206999239","https://openalex.org/W2161928627","https://openalex.org/W4388482952","https://openalex.org/W2786113878","https://openalex.org/W2727867943","https://openalex.org/W3015562293","https://openalex.org/W4400860681","https://openalex.org/W1978161581","https://openalex.org/W2787155073"],"abstract_inverted_index":{"In":[0],"the":[1,22,57,63,75,81,100,113,135,140,147,171],"last":[2],"decade,":[3],"industry\u2019s":[4],"demand":[5],"for":[6],"deep":[7],"learning":[8],"(DL)":[9],"has":[10],"increased":[11],"due":[12],"to":[13,21,74,92,155,185],"its":[14],"high":[15],"performance":[16,77,163],"in":[17,54,62,88,94,105],"complex":[18],"scenarios.":[19],"Due":[20],"DL":[23],"method\u2019s":[24],"complexity,":[25],"experts":[26],"and":[27,37,44,65],"non-experts":[28],"rely":[29],"on":[30,112],"blackbox":[31],"software":[32,55,183],"packages":[33],"such":[34,177],"as":[35,178],"Tensorflow":[36],"Pytorch.":[38],"The":[39,85],"frameworks":[40,111],"are":[41,47],"constantly":[42],"improving,":[43],"new":[45],"versions":[46,59,69],"released":[48,58],"frequently.":[49],"As":[50],"a":[51,121,150,165,182],"natural":[52],"process":[53],"development,":[56],"contain":[60],"improvements/changes":[61],"methods":[64],"their":[66],"implementation.":[67],"Moreover,":[68,143],"may":[70],"be":[71],"bug-polluted,":[72],"leading":[73],"model":[76,82,114,141],"decreasing":[78],"or":[79],"stopping":[80],"from":[83],"working.":[84],"aforementioned":[86],"changes":[87,104],"implementation":[89,103],"can":[90,138],"lead":[91],"variance":[93],"obtained":[95],"results.":[96],"This":[97,168],"work":[98],"investigates":[99],"effect":[101],"of":[102,109,123,149,173],"different":[106],"major":[107],"releases":[108],"these":[110],"performance.":[115,142],"We":[116],"perform":[117],"our":[118],"study":[119,127],"using":[120,174],"variety":[122],"standard":[124],"datasets.":[125],"Our":[126],"shows":[128,170],"that":[129,133,159],"users":[130],"should":[131,145],"consider":[132,146],"changing":[134],"framework":[136],"version":[137,152,166],"affect":[139],"they":[144],"possibility":[148],"bug-polluted":[151],"before":[153,164],"starting":[154],"debug":[156],"source":[157],"code":[158],"had":[160],"an":[161],"excellent":[162],"change.":[167],"also":[169],"importance":[172],"virtual":[175],"environments,":[176],"Docker,":[179],"when":[180],"delivering":[181],"product":[184],"clients.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2022-10-09T00:00:00"}