{"id":"https://openalex.org/W4415744253","doi":"https://doi.org/10.1109/qrs-c65679.2025.00056","title":"SACCD: Semantic Alignment-based Cross-language Code Clone Detection","display_name":"SACCD: Semantic Alignment-based Cross-language Code Clone Detection","publication_year":2025,"publication_date":"2025-07-16","ids":{"openalex":"https://openalex.org/W4415744253","doi":"https://doi.org/10.1109/qrs-c65679.2025.00056"},"language":null,"primary_location":{"id":"doi:10.1109/qrs-c65679.2025.00056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qrs-c65679.2025.00056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 25th International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","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/A5100621723","display_name":"Zeng You","orcid":"https://orcid.org/0009-0000-3808-5650"},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"You Zeng","raw_affiliation_strings":["Jiangsu Normal University,Xuzhou,China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Normal University,Xuzhou,China","institution_ids":["https://openalex.org/I118574674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018269253","display_name":"Chunli Xie","orcid":"https://orcid.org/0000-0002-1490-2991"},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunli Xie","raw_affiliation_strings":["Jiangsu Normal University,Xuzhou,China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Normal University,Xuzhou,China","institution_ids":["https://openalex.org/I118574674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101634827","display_name":"Y. Hu","orcid":"https://orcid.org/0009-0007-7133-2650"},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanfa Hu","raw_affiliation_strings":["Jiangsu Normal University,Xuzhou,China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Normal University,Xuzhou,China","institution_ids":["https://openalex.org/I118574674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100451684","display_name":"Yuqi Wang","orcid":"https://orcid.org/0000-0002-8008-7294"},"institutions":[{"id":"https://openalex.org/I118574674","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I118574674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqi Wang","raw_affiliation_strings":["Jiangsu Normal University,Xuzhou,China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Normal University,Xuzhou,China","institution_ids":["https://openalex.org/I118574674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100621723"],"corresponding_institution_ids":["https://openalex.org/I118574674"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45032575,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"390","last_page":"399"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.8596000075340271,"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":0.8596000075340271,"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":0.07029999792575836,"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/T12380","display_name":"Authorship Attribution and Profiling","score":0.008700000122189522,"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/syntax","display_name":"Syntax","score":0.5741000175476074},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.505299985408783},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.492900013923645},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4553999900817871},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.44440001249313354},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4408999979496002},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.41769999265670776},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.41600000858306885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8129000067710876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6215000152587891},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.5741000175476074},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.505299985408783},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.492900013923645},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.46950000524520874},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4553999900817871},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.44440001249313354},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4408999979496002},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.41769999265670776},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.41600000858306885},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.36970001459121704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35830000042915344},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C198942812","wikidata":"https://www.wikidata.org/wiki/Q496618","display_name":"Semantic property","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C67277372","wikidata":"https://www.wikidata.org/wiki/Q7449085","display_name":"Semantic role labeling","level":3,"score":0.2567000091075897},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/qrs-c65679.2025.00056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qrs-c65679.2025.00056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 25th International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322298","display_name":"Jiangsu Normal University","ror":"https://ror.org/051hvcm98"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2128782367","https://openalex.org/W2585680471","https://openalex.org/W2598761292","https://openalex.org/W2606310092","https://openalex.org/W2796335629","https://openalex.org/W2807866521","https://openalex.org/W2808509424","https://openalex.org/W2899171197","https://openalex.org/W2955127311","https://openalex.org/W2962739339","https://openalex.org/W3000135256","https://openalex.org/W3089944807","https://openalex.org/W3096144872","https://openalex.org/W3098605233","https://openalex.org/W4221166942","https://openalex.org/W4226463316","https://openalex.org/W4312465319","https://openalex.org/W4312690534","https://openalex.org/W4320060335","https://openalex.org/W4385570138","https://openalex.org/W4386472818","https://openalex.org/W4388483231"],"related_works":[],"abstract_inverted_index":{"In":[0],"multilingual":[1],"development,":[2],"cross-language":[3,132],"code":[4,13,133],"clone":[5,163],"detection":[6,104],"plays":[7],"a":[8,23,62,67,85,127,136,158],"crucial":[9],"role":[10,191],"in":[11,28,135,199],"enhancing":[12,103],"reuse,":[14],"maintenance":[15],"efficiency":[16],"and":[17,30,54,91,106,121,173,179,197,207,209],"security.":[18],"However,":[19],"semantic":[20,92,97,138,194],"consistency":[21],"remains":[22],"challenge":[24],"due":[25],"to":[26,74,94,130,147],"differences":[27],"syntax":[29],"structure":[31,153],"among":[32],"programming":[33],"languages.":[34],"Existing":[35],"methods,":[36],"such":[37],"as":[38],"C4,":[39],"directly":[40],"perform":[41],"contrastive":[42,145],"learning":[43,146],"on":[44,61,212],"the":[45,71,111,149,189,193],"encoder":[46],"weights.":[47],"These":[48],"approaches":[49],"may":[50],"introduce":[51,83],"irrelevant":[52],"features":[53,98],"noise.":[55],"Additionally,":[56,201],"these":[57],"methods":[58],"typically":[59],"rely":[60],"single":[63],"positive":[64,119],"sample":[65],"at":[66],"time,":[68],"which":[69],"restricts":[70],"model\u2019s":[72],"capacity":[73],"capture":[75,95],"comprehensive":[76],"semantics.":[77],"To":[78],"address":[79],"this":[80,202],"problem,":[81],"we":[82,109,156],"SACCD,":[84],"method":[86],"that":[87,168],"employs":[88],"feature":[89],"mapping":[90],"alignment":[93,195],"deep":[96],"across":[99],"different":[100],"languages,":[101],"thereby":[102],"accuracy":[105],"generalization.":[107],"First,":[108],"reconstruct":[110],"original":[112],"samples":[113],"into":[114],"triplets":[115],"consisting":[116],"of":[117,151,176,192],"anchors,":[118],"samples,":[120],"negative":[122],"samples.":[123],"Next,":[124],"We":[125],"propose":[126],"projection":[128],"head":[129],"align":[131],"snippets":[134],"unified":[137],"space.":[139],"This":[140],"space":[141],"is":[142],"optimized":[143],"through":[144],"mitigate":[148],"impact":[150],"syntactic":[152],"differences.":[154],"Finally,":[155],"employ":[157],"multilayer":[159],"perceptron":[160],"(MLP)":[161],"for":[162],"detection.The":[164],"experimental":[165],"results":[166],"show":[167],"SACCD":[169],"achieves":[170],"accuracy,":[171],"recall,":[172],"F1":[174],"scores":[175],"0.99,":[177],"0.97,":[178],"0.98,":[180],"respectively,":[181],"significantly":[182],"outperforming":[183],"existing":[184],"methods.":[185],"Ablation":[186],"experiments":[187,211,220],"confirm":[188],"critical":[190],"strategy":[196],"MLP":[198],"SACCD.":[200],"study":[203],"evaluates":[204],"various":[205],"encoders":[206],"classifiers":[208],"conducts":[210],"imbalanced":[213],"language":[214],"combinations":[215],"within":[216],"datasets,":[217],"with":[218],"all":[219],"yielding":[221],"good":[222],"results.":[223]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-31T00:00:00"}