{"id":"https://openalex.org/W4312568075","doi":"https://doi.org/10.1145/3524610.3527894","title":"Self-supervised learning of smart contract representations","display_name":"Self-supervised learning of smart contract representations","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4312568075","doi":"https://doi.org/10.1145/3524610.3527894"},"language":"en","primary_location":{"id":"doi:10.1145/3524610.3527894","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3524610.3527894","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension","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/A5100586253","display_name":"Shouliang Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shouliang Yang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033286111","display_name":"Xiaodong Gu","orcid":"https://orcid.org/0000-0002-0529-6408"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Gu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045672909","display_name":"Beijun Shen","orcid":"https://orcid.org/0000-0001-8370-3956"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Beijun Shen","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"82","last_page":"93"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9997000098228455,"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":0.9997000098228455,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9459999799728394,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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":0.7839412689208984},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5802544951438904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5513612031936646},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5412144660949707},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4957159757614136},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47395801544189453},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4516840875148773},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.411062628030777},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.17571470141410828}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7839412689208984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5802544951438904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5513612031936646},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5412144660949707},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4957159757614136},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47395801544189453},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4516840875148773},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.411062628030777},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.17571470141410828},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3524610.3527894","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3524610.3527894","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6399999856948853}],"awards":[{"id":"https://openalex.org/G3174597492","display_name":null,"funder_award_id":"Grant No. 62102244, 62032004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W893234787","https://openalex.org/W1968882522","https://openalex.org/W2018663431","https://openalex.org/W2068470708","https://openalex.org/W2161160262","https://openalex.org/W2187089797","https://openalex.org/W2251658415","https://openalex.org/W2493916176","https://openalex.org/W2540162589","https://openalex.org/W2592249290","https://openalex.org/W2735043505","https://openalex.org/W2747329762","https://openalex.org/W2789962766","https://openalex.org/W2794601162","https://openalex.org/W2884276923","https://openalex.org/W2887364112","https://openalex.org/W2891649471","https://openalex.org/W2955426500","https://openalex.org/W2963216553","https://openalex.org/W2964150020","https://openalex.org/W3001458527","https://openalex.org/W3035282664","https://openalex.org/W3035352537","https://openalex.org/W3084421431","https://openalex.org/W3098605233","https://openalex.org/W3104038788","https://openalex.org/W3162689995","https://openalex.org/W3162962341","https://openalex.org/W3165214486","https://openalex.org/W3175000455","https://openalex.org/W3215134427","https://openalex.org/W4205371973","https://openalex.org/W4237040408","https://openalex.org/W4239019441","https://openalex.org/W6745136726"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W4205302943","https://openalex.org/W2561132942","https://openalex.org/W3155418658","https://openalex.org/W4243199227","https://openalex.org/W2379948177","https://openalex.org/W2515319207"],"abstract_inverted_index":{"Learning":[0],"smart":[1,10,33,58,87,117,127],"contract":[2,59],"representations":[3,27],"can":[4],"greatly":[5],"facilitate":[6],"the":[7,106,139],"development":[8],"of":[9,80,86,116,125],"contracts":[11,34,128],"in":[12,46],"many":[13],"tasks":[14],"such":[15],"as":[16],"bug":[17],"detection":[18],"and":[19,39,83,112],"clone":[20],"detection.":[21],"Existing":[22],"approaches":[23],"for":[24,56],"learning":[25,57,79],"program":[26],"are":[28,66,102],"difficult":[29],"to":[30,32,104,109],"apply":[31],"which":[35,65],"have":[36],"insufficient":[37],"data":[38,70,76],"significant":[40],"homogenization.":[41],"To":[42],"overcome":[43],"these":[44],"challenges,":[45],"this":[47],"paper,":[48],"we":[49],"propose":[50],"SRCL,":[51],"a":[52,123],"novel,":[53],"self-supervised":[54,78],"approach":[55],"representations.":[60],"Unlike":[61],"existing":[62],"supervised":[63],"methods,":[64],"tied":[67],"on":[68,122,144],"task-specific":[69],"labels,":[71],"SRCL":[72,121,136],"leverages":[73],"large-scale":[74],"unlabeled":[75],"by":[77],"both":[81],"local":[82,111],"global":[84,113],"information":[85],"contracts.":[88,118],"It":[89],"automatically":[90],"extracts":[91],"structural":[92],"sequences":[93],"from":[94,130],"abstract":[95],"syntax":[96],"trees":[97],"(ASTs).":[98],"Then,":[99],"two":[100],"discriminators":[101],"designed":[103],"guide":[105],"Transformer":[107],"encoder":[108],"learn":[110],"semantic":[114],"features":[115],"We":[119],"evaluate":[120],"dataset":[124],"75,006":[126],"collected":[129],"Etherscan.":[131],"Experimental":[132],"results":[133],"show":[134],"that":[135],"considerably":[137],"outperforms":[138],"state-of-the-art":[140],"code":[141],"representation":[142],"models":[143],"three":[145],"downstream":[146],"tasks.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}