{"id":"https://openalex.org/W2971899238","doi":"https://doi.org/10.1145/3355378.3355379","title":"Structure verification of deep neural networks at compilation time using dependent types","display_name":"Structure verification of deep neural networks at compilation time using dependent types","publication_year":2019,"publication_date":"2019-09-05","ids":{"openalex":"https://openalex.org/W2971899238","doi":"https://doi.org/10.1145/3355378.3355379","mag":"2971899238"},"language":"en","primary_location":{"id":"doi:10.1145/3355378.3355379","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3355378.3355379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the XXIII Brazilian Symposium on Programming Languages","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/A5044869911","display_name":"Leonardo Pi\u00f1eyro","orcid":null},"institutions":[{"id":"https://openalex.org/I180910786","display_name":"Universidad de la Rep\u00fablica","ror":"https://ror.org/030bbe882","country_code":"UY","type":"education","lineage":["https://openalex.org/I180910786"]}],"countries":["UY"],"is_corresponding":true,"raw_author_name":"Leonardo Pi\u00f1eyro","raw_affiliation_strings":["Instituto de Computaci\u00f3n, Universidad de la Rep\u00fablica, Montevideo, Uruguay"],"affiliations":[{"raw_affiliation_string":"Instituto de Computaci\u00f3n, Universidad de la Rep\u00fablica, Montevideo, Uruguay","institution_ids":["https://openalex.org/I180910786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007307934","display_name":"Alberto Pardo","orcid":"https://orcid.org/0000-0003-4011-4232"},"institutions":[{"id":"https://openalex.org/I180910786","display_name":"Universidad de la Rep\u00fablica","ror":"https://ror.org/030bbe882","country_code":"UY","type":"education","lineage":["https://openalex.org/I180910786"]}],"countries":["UY"],"is_corresponding":false,"raw_author_name":"Alberto Pardo","raw_affiliation_strings":["Instituto de Computaci\u00f3n, Universidad de la Rep\u00fablica, Montevideo, Uruguay"],"affiliations":[{"raw_affiliation_string":"Instituto de Computaci\u00f3n, Universidad de la Rep\u00fablica, Montevideo, Uruguay","institution_ids":["https://openalex.org/I180910786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026040673","display_name":"Marcos Viera","orcid":"https://orcid.org/0000-0003-2291-6151"},"institutions":[{"id":"https://openalex.org/I180910786","display_name":"Universidad de la Rep\u00fablica","ror":"https://ror.org/030bbe882","country_code":"UY","type":"education","lineage":["https://openalex.org/I180910786"]}],"countries":["UY"],"is_corresponding":false,"raw_author_name":"Marcos Viera","raw_affiliation_strings":["Instituto de Computaci\u00f3n, Universidad de la Rep\u00fablica, Montevideo, Uruguay"],"affiliations":[{"raw_affiliation_string":"Instituto de Computaci\u00f3n, Universidad de la Rep\u00fablica, Montevideo, Uruguay","institution_ids":["https://openalex.org/I180910786"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5044869911"],"corresponding_institution_ids":["https://openalex.org/I180910786"],"apc_list":null,"apc_paid":null,"fwci":0.1447,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.58101659,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"46","last_page":"53"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9944999814033508,"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/T11424","display_name":"Security and Verification in Computing","score":0.9943000078201294,"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":0.8401157855987549},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7267173528671265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6946877241134644},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.6727147698402405},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6594818234443665},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6558054685592651},{"id":"https://openalex.org/keywords/haskell","display_name":"Haskell","score":0.6362226605415344},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5955490469932556},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45224839448928833},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4199845492839813},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.3706032633781433},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.34920671582221985},{"id":"https://openalex.org/keywords/functional-programming","display_name":"Functional programming","score":0.27950459718704224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8401157855987549},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7267173528671265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6946877241134644},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.6727147698402405},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6594818234443665},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6558054685592651},{"id":"https://openalex.org/C2780624054","wikidata":"https://www.wikidata.org/wiki/Q34010","display_name":"Haskell","level":3,"score":0.6362226605415344},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5955490469932556},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45224839448928833},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4199845492839813},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.3706032633781433},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.34920671582221985},{"id":"https://openalex.org/C42383842","wikidata":"https://www.wikidata.org/wiki/Q193076","display_name":"Functional programming","level":2,"score":0.27950459718704224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3355378.3355379","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3355378.3355379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the XXIII Brazilian Symposium on Programming Languages","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1995675054","https://openalex.org/W2007339694","https://openalex.org/W2096118443","https://openalex.org/W2112474400","https://openalex.org/W2125908420","https://openalex.org/W2148461049","https://openalex.org/W2156285626","https://openalex.org/W2194775991","https://openalex.org/W2543296129","https://openalex.org/W2763618583","https://openalex.org/W2784620461","https://openalex.org/W2899771611","https://openalex.org/W2919115771","https://openalex.org/W2953384591","https://openalex.org/W3103114563","https://openalex.org/W4253057161","https://openalex.org/W6713134421"],"related_works":["https://openalex.org/W1601811574","https://openalex.org/W1587224678","https://openalex.org/W2947175736","https://openalex.org/W1967226206","https://openalex.org/W2192862863","https://openalex.org/W2482620160","https://openalex.org/W2129335813","https://openalex.org/W1567780099","https://openalex.org/W4287510235","https://openalex.org/W2597787948"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"TensorSafe,":[3],"a":[4,81,93],"dependently":[5],"typed":[6],"Haskell":[7],"library":[8],"which":[9,84],"makes":[10],"possible":[11,175],"the":[12,23,36,42,59,71,86,129,134,137,142,152,158,161],"definition":[13],"and":[14,66,141,155],"structural":[15,101],"validation":[16,88],"of":[17,26,38,46,73,89,107,117,131,136,144,148,160],"deep":[18,27,74,94,181],"neural":[19,75,119,162,182],"networks":[20,76,120],"architectures.":[21],"Nowadays,":[22],"development":[24,153],"process":[25,154],"learning":[28,95],"models":[29],"has":[30],"been":[31],"notably":[32],"simplified":[33],"due":[34],"to":[35,111,156,176],"availability":[37],"sophisticated":[39],"tools":[40,48],"in":[41,128],"industry.":[43],"However,":[44],"most":[45],"these":[47],"do":[49],"not":[50],"provide":[51],"any":[52],"security":[53],"controls":[54],"at":[55,77],"compilation":[56,78],"time,":[57],"making":[58],"developers":[60],"deal":[61],"with":[62],"unexpected":[63],"run-time":[64],"errors":[65],"uncertainties.":[67],"In":[68],"particular,":[69],"validating":[70],"structure":[72],"time":[79],"is":[80,174],"complex":[82],"subject":[83],"involves":[85],"mathematical":[87],"all":[90],"operations":[91],"that":[92,169],"model":[96],"will":[97],"perform.":[98],"Moreover,":[99],"this":[100],"checking":[102],"requires":[103],"an":[104],"advanced":[105],"usage":[106],"types":[108,146],"systems":[109],"theories":[110],"manipulate":[112],"abstract":[113],"type":[114],"definitions":[115],"capable":[116],"modeling":[118],"constructions.":[121],"Many":[122],"different":[123],"programming":[124,139],"techniques":[125],"were":[126,147],"involved":[127],"specification":[130],"TensorSafe.":[132],"Primarily,":[133],"application":[135],"functional":[138],"paradigm":[140],"use":[143],"dependent":[145],"great":[149],"importance":[150],"for":[151],"probe":[157],"correctness":[159],"network":[163,183],"models.":[164],"The":[165],"experimental":[166],"evaluation":[167],"showed":[168],"by":[170],"using":[171],"TensorSafe":[172],"it":[173],"correctly":[177],"create":[178],"well":[179],"known":[180],"architectures,":[184],"such":[185],"like":[186],"MNIST":[187],"or":[188],"ResNet50.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
