{"id":"https://openalex.org/W4384154537","doi":"https://doi.org/10.1145/3597926.3598143","title":"Third-Party Library Dependency for Large-Scale SCA in the C/C++ Ecosystem: How Far Are We?","display_name":"Third-Party Library Dependency for Large-Scale SCA in the C/C++ Ecosystem: How Far Are We?","publication_year":2023,"publication_date":"2023-07-12","ids":{"openalex":"https://openalex.org/W4384154537","doi":"https://doi.org/10.1145/3597926.3598143"},"language":"en","primary_location":{"id":"doi:10.1145/3597926.3598143","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3597926.3598143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis","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/A5023059086","display_name":"Ling Jiang","orcid":"https://orcid.org/0000-0001-5175-6615"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Jiang","raw_affiliation_strings":["Southern University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104142912","display_name":"Hengchen Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengchen Yuan","raw_affiliation_strings":["Southern University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007842132","display_name":"Qiyi Tang","orcid":"https://orcid.org/0000-0002-8200-7518"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiyi Tang","raw_affiliation_strings":["Tencent Security Keen Lab, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Security Keen Lab, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069450513","display_name":"Sen Nie","orcid":"https://orcid.org/0000-0003-4154-2941"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Nie","raw_affiliation_strings":["Tencent Security Keen Lab, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Security Keen Lab, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101409340","display_name":"Shi Wu","orcid":"https://orcid.org/0000-0002-6842-7487"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi Wu","raw_affiliation_strings":["Tencent Security Keen Lab, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent Security Keen Lab, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030322956","display_name":"Yuqun Zhang","orcid":"https://orcid.org/0000-0002-1499-5729"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqun Zhang","raw_affiliation_strings":["Southern University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern University of Science and Technology, China","institution_ids":["https://openalex.org/I3045169105"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.2975,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.98413175,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1383","last_page":"1395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9998000264167786,"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":0.9998000264167786,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9853000044822693,"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/computer-science","display_name":"Computer science","score":0.7184699773788452},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.5181328058242798},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5059646964073181},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.473755419254303},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4638391137123108},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.43486765027046204},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.43261855840682983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4112064838409424},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3301035165786743},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3084023594856262},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19813641905784607},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14306116104125977},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09874588251113892},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.08883845806121826}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7184699773788452},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.5181328058242798},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5059646964073181},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.473755419254303},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4638391137123108},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.43486765027046204},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.43261855840682983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4112064838409424},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3301035165786743},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3084023594856262},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19813641905784607},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14306116104125977},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09874588251113892},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.08883845806121826},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3597926.3598143","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3597926.3598143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G1308942226","display_name":null,"funder_award_id":"2020B121201001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3814908347","display_name":null,"funder_award_id":"KQTD2016112514355531","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G521923880","display_name":null,"funder_award_id":"KQTD2016112514355531","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5511685887","display_name":null,"funder_award_id":"61902169","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"},{"id":"https://openalex.org/F4320335790","display_name":"Shenzhen Peacock Plan","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W165416599","https://openalex.org/W1976596267","https://openalex.org/W2008105577","https://openalex.org/W2017975254","https://openalex.org/W2021963610","https://openalex.org/W2024671287","https://openalex.org/W2026417691","https://openalex.org/W2040906208","https://openalex.org/W2128782367","https://openalex.org/W2132944054","https://openalex.org/W2400269587","https://openalex.org/W2532717356","https://openalex.org/W2559865276","https://openalex.org/W2594655792","https://openalex.org/W2613498170","https://openalex.org/W2618014206","https://openalex.org/W2740721704","https://openalex.org/W2741068848","https://openalex.org/W2741705590","https://openalex.org/W2749008552","https://openalex.org/W2766078311","https://openalex.org/W2898435572","https://openalex.org/W2899171197","https://openalex.org/W2911282308","https://openalex.org/W2949130492","https://openalex.org/W2955426500","https://openalex.org/W2957010138","https://openalex.org/W3015384571","https://openalex.org/W3043078865","https://openalex.org/W3045279034","https://openalex.org/W3098380913","https://openalex.org/W3105926539","https://openalex.org/W3121452324","https://openalex.org/W3122252170","https://openalex.org/W3125205154","https://openalex.org/W3212083716","https://openalex.org/W4210788642","https://openalex.org/W4224245093","https://openalex.org/W4235670907","https://openalex.org/W4236479165","https://openalex.org/W4240306659","https://openalex.org/W4250866398","https://openalex.org/W4253813365","https://openalex.org/W4254624923","https://openalex.org/W4284679382","https://openalex.org/W4284690592","https://openalex.org/W4284714607","https://openalex.org/W4285490409","https://openalex.org/W4285490465","https://openalex.org/W4297648349","https://openalex.org/W4298112463","https://openalex.org/W4301168982"],"related_works":["https://openalex.org/W2327631927","https://openalex.org/W2093568763","https://openalex.org/W69297589","https://openalex.org/W1985166372","https://openalex.org/W2003096546","https://openalex.org/W4289354592","https://openalex.org/W2430210575","https://openalex.org/W2165069859","https://openalex.org/W2099112646","https://openalex.org/W2112258778"],"abstract_inverted_index":{"Existing":[0],"software":[1,21],"composition":[2],"analysis":[3],"(SCA)":[4],"techniques":[5],"for":[6,50,67,126],"the":[7,13,51,64,69,83,86,89,97,101,113,128,144,149,168,173,177,183,188,193,221,228,239,246,262,269,277,286,294,301],"C/C++":[8,52,229],"ecosystem":[9],"tend":[10],"to":[11,56,62,99,161,219,243,250,266,273,298,305],"identify":[12],"reused":[14],"components":[15],"through":[16],"feature":[17,29],"matching":[18],"between":[19],"target":[20],"project":[22],"and":[23,115,134,182,215,245,268,283,300],"collected":[24],"third-party":[25],"libraries":[26],"(TPLs).":[27],"However,":[28],"duplication":[30],"caused":[31],"by":[32,155,197,204],"internal":[33],"code":[34,59],"clone":[35,60],"can":[36,175,199],"cause":[37],"inaccurate":[38,178],"SCA":[39,48,74,107,135,191,280,289],"results.":[40],"To":[41,110],"mitigate":[42],"this":[43],"issue,":[44],"Centris,":[45,118],"a":[46],"state-of-the-art":[47],"technique":[49],"ecosystem,":[53],"was":[54],"proposed":[55],"adopt":[57],"function-level":[58,211],"detection":[61,214,226],"derive":[63],"TPL":[65,91,104,132,152,194,213,224,254],"dependencies":[66,92,153,195,255],"eliminating":[68],"redundant":[70],"features":[71],"before":[72],"performing":[73],"tasks.":[75],"Although":[76],"Centris":[77,142,156,198],"has":[78],"been":[79],"shown":[80],"effective":[81],"in":[82,227],"original":[84],"paper,":[85],"accuracy":[87,129,150,222],"of":[88,103,117,130,151,223,252],"derived":[90,154,196],"is":[93,108],"not":[94,158],"evaluated.":[95],"Additionally,":[96],"dataset":[98],"evaluate":[100,141],"impact":[102,189],"dependency":[105,133,217],"on":[106,190],"limited.":[109,202],"further":[111,166],"investigate":[112],"efficacy":[114],"limitations":[116],"we":[119,139,207],"first":[120],"construct":[121],"two":[122],"large-scale":[123],"ground-truth":[124],"datasets":[125],"evaluating":[127],"deriving":[131,253],"results":[136,146,233],"respectively.":[137],"Then":[138],"extensively":[140],"where":[143],"evaluation":[145,163,232],"suggest":[147],"that":[148,171,235],"may":[157],"well":[159],"generalize":[160],"our":[162,205],"dataset.":[164],"We":[165],"infer":[167],"key":[169],"factors":[170],"degrade":[172],"performance":[174],"be":[176,200],"function":[179],"birth":[180],"time":[181],"threshold-based":[184],"recall.":[185],"In":[186],"addition,":[187],"from":[192,241,248,264,271,296,303],"somewhat":[201],"Inspired":[203],"findings,":[206],"propose":[208],"TPLite":[209,236,260],"with":[210,257,276],"origin":[212],"graph-based":[216],"recall":[218,247,270,302],"enhance":[220],"reuse":[225],"ecosystem.":[230],"Our":[231],"indicate":[234],"effectively":[237],"increases":[238,261],"precision":[240,263,295],"35.71%":[242],"88.33%":[244],"49.44%":[249],"62.65%":[251],"compared":[256,275],"Centris.":[258],"Moreover,":[259],"21.08%":[265],"75.90%":[267,299],"57.62%":[272],"64.17%":[274],"SOTA":[278],"academic":[279],"tool":[281,290],"B2SFinder":[282],"even":[284],"outperforms":[285],"well-adopted":[287],"commercial":[288],"BDBA,":[291],"i.e.,":[292],"increasing":[293],"72.46%":[297],"58.55%":[304],"64.17%.":[306]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2025-10-10T00:00:00"}
