{"id":"https://openalex.org/W2312398278","doi":"https://doi.org/10.1109/tse.2016.2543218","title":"HYDRA: Massively Compositional Model for Cross-Project Defect Prediction","display_name":"HYDRA: Massively Compositional Model for Cross-Project Defect Prediction","publication_year":2016,"publication_date":"2016-03-17","ids":{"openalex":"https://openalex.org/W2312398278","doi":"https://doi.org/10.1109/tse.2016.2543218","mag":"2312398278"},"language":"en","primary_location":{"id":"doi:10.1109/tse.2016.2543218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tse.2016.2543218","pdf_url":null,"source":{"id":"https://openalex.org/S8351582","display_name":"IEEE Transactions on Software Engineering","issn_l":"0098-5589","issn":["0098-5589","1939-3520","2326-3881"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Software Engineering","raw_type":"journal-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/A5006669765","display_name":"Xin Xia","orcid":"https://orcid.org/0000-0002-6302-3256"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Xia","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081036622","display_name":"David Lo","orcid":"https://orcid.org/0000-0002-4367-7201"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"David Lo","raw_affiliation_strings":["School of Information Systems, Singapore Management University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Information Systems, Singapore Management University, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082984558","display_name":"Sinno Jialin Pan","orcid":"https://orcid.org/0000-0001-6565-3836"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Sinno Jialin Pan","raw_affiliation_strings":["School of Computer Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101612061","display_name":"Nachiappan Nagappan","orcid":"https://orcid.org/0000-0003-1358-4124"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nachiappan Nagappan","raw_affiliation_strings":["Testing, Verification and Measurement Research, Microsoft Research, Redmond, WA"],"affiliations":[{"raw_affiliation_string":"Testing, Verification and Measurement Research, Microsoft Research, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100352800","display_name":"Xinyu Wang","orcid":"https://orcid.org/0000-0002-5507-6569"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Wang","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I168879160"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5006669765"],"corresponding_institution_ids":["https://openalex.org/I168879160"],"apc_list":null,"apc_paid":null,"fwci":75.9543,"has_fulltext":false,"cited_by_count":287,"citation_normalized_percentile":{"value":0.99929291,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"42","issue":"10","first_page":"977","last_page":"998"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":1.0,"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":1.0,"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/T12423","display_name":"Software Reliability and Analysis Research","score":0.9926000237464905,"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"}},{"id":"https://openalex.org/T10430","display_name":"Software Engineering Techniques and Practices","score":0.9814000129699707,"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":0.7706049084663391},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.5072941184043884},{"id":"https://openalex.org/keywords/software-bug","display_name":"Software bug","score":0.46139857172966003},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4329725503921509},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4326176345348358},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.42211028933525085},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4151979982852936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4074890613555908},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.13448935747146606}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7706049084663391},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.5072941184043884},{"id":"https://openalex.org/C1009929","wikidata":"https://www.wikidata.org/wiki/Q179550","display_name":"Software bug","level":3,"score":0.46139857172966003},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4329725503921509},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4326176345348358},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.42211028933525085},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4151979982852936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4074890613555908},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.13448935747146606},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tse.2016.2543218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tse.2016.2543218","pdf_url":null,"source":{"id":"https://openalex.org/S8351582","display_name":"IEEE Transactions on Software Engineering","issn_l":"0098-5589","issn":["0098-5589","1939-3520","2326-3881"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Software Engineering","raw_type":"journal-article"},{"id":"pmh:oai:ink.library.smu.edu.sg:sis_research-4416","is_oa":false,"landing_page_url":"https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=4416&amp;amp;context=sis_research","pdf_url":null,"source":{"id":"https://openalex.org/S4377196871","display_name":"Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79891267","host_organization_name":"Singapore Management University","host_organization_lineage":["https://openalex.org/I79891267"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://doi.ieeecomputersociety.org/10.1109/TSE.2016.2543218","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5}],"awards":[{"id":"https://openalex.org/G2039607704","display_name":null,"funder_award_id":"2015CB352201","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7601051823","display_name":null,"funder_award_id":"61572426","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W168970045","https://openalex.org/W259338706","https://openalex.org/W605727707","https://openalex.org/W1506806321","https://openalex.org/W1541288193","https://openalex.org/W1553010236","https://openalex.org/W1553313034","https://openalex.org/W1601795611","https://openalex.org/W1785944873","https://openalex.org/W1902482618","https://openalex.org/W1953529280","https://openalex.org/W1961761736","https://openalex.org/W1964544799","https://openalex.org/W1964962870","https://openalex.org/W1975846642","https://openalex.org/W1978859404","https://openalex.org/W1980851144","https://openalex.org/W1988019447","https://openalex.org/W1988790447","https://openalex.org/W1992345889","https://openalex.org/W2006700268","https://openalex.org/W2010398592","https://openalex.org/W2019298113","https://openalex.org/W2021688474","https://openalex.org/W2025700486","https://openalex.org/W2033418259","https://openalex.org/W2040900804","https://openalex.org/W2046830558","https://openalex.org/W2066477694","https://openalex.org/W2068430427","https://openalex.org/W2074218040","https://openalex.org/W2094764356","https://openalex.org/W2101227285","https://openalex.org/W2107323945","https://openalex.org/W2110656807","https://openalex.org/W2111362445","https://openalex.org/W2114191341","https://openalex.org/W2115403315","https://openalex.org/W2122702470","https://openalex.org/W2122838776","https://openalex.org/W2128182542","https://openalex.org/W2130883460","https://openalex.org/W2133990480","https://openalex.org/W2135198476","https://openalex.org/W2136706100","https://openalex.org/W2138428785","https://openalex.org/W2138661194","https://openalex.org/W2140190241","https://openalex.org/W2144177913","https://openalex.org/W2150874999","https://openalex.org/W2158744032","https://openalex.org/W2158864412","https://openalex.org/W2160958420","https://openalex.org/W2163732854","https://openalex.org/W2165698076","https://openalex.org/W2167363007","https://openalex.org/W2172232422","https://openalex.org/W2212983101","https://openalex.org/W3141218678","https://openalex.org/W3141989311","https://openalex.org/W3142656464","https://openalex.org/W4206600618","https://openalex.org/W4238859253","https://openalex.org/W4252684946","https://openalex.org/W6640768872","https://openalex.org/W6677069268","https://openalex.org/W6688621198"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2961085424","https://openalex.org/W3043432080","https://openalex.org/W4317600379","https://openalex.org/W3106528173","https://openalex.org/W3158675493","https://openalex.org/W2184352032","https://openalex.org/W3216967183","https://openalex.org/W2022585969","https://openalex.org/W4381185318"],"abstract_inverted_index":{"Most":[0],"software":[1],"defect":[2,27,47,62,139],"prediction":[3,140],"approaches":[4,325],"are":[5,340,348],"trained":[6],"and":[7,72,163,201,210,300,330,342,350],"applied":[8],"on":[9,95,216],"data":[10,31],"from":[11,32,98],"the":[12,88,99,123,134,183,193,228,237,251,258,274,295,308,312,318,333,346,356],"same":[13],"project.":[14],"However,":[15],"often":[16],"a":[17,39,43,54,81,104],"new":[18,44],"project":[19],"does":[20],"not":[21],"have":[22,303,351],"enough":[23],"training":[24],"data.":[25],"Cross-project":[26],"prediction,":[28,63],"which":[29,64,102,235,255],"uses":[30],"other":[33,323],"projects":[34],"to":[35,46,189,260,287,297,304,310],"predict":[36,256],"defects":[37],"in":[38,192,326,343],"particular":[40],"project,":[41],"provides":[42],"perspective":[45],"prediction.":[48],"In":[49,213,281],"this":[50],"work,":[51],"we":[52,92,316],"propose":[53],"HYbrid":[55],"moDel":[56],"Reconstruction":[57],"Approach":[58],"(HYDRA)":[59],"for":[60],"cross-project":[61,138],"includes":[65],"two":[66,78],"phases:":[67],"genetic":[68],"algorithm":[69,126],"(GA)":[70],"phase":[71],"ensemble":[73],"learning":[74],"(EL)":[75],"phase.":[76],"These":[77],"phases":[79],"create":[80],"massive":[82],"composition":[83],"of":[84,90,106,127,178,195,222,233,253,279,294,307,320,328,338],"classifiers.":[85],"To":[86],"examine":[87],"benefits":[89],"HYDRA,":[91],"perform":[93],"experiments":[94],"29":[96,184,357],"datasets":[97],"PROMISE":[100],"repository":[101],"contains":[103],"total":[105],"11,196":[107],"instances":[108,259,296,309],"(i.e.,":[109],"Java":[110],"classes)":[111],"labeled":[112],"as":[113,122],"defective":[114,262,313],"or":[115],"clean.":[116],"We":[117,129,245],"experiment":[118],"with":[119,133],"logistic":[120],"regression":[121],"underlying":[124],"classification":[125],"HYDRA.":[128],"compare":[130],"our":[131],"approach":[132,240],"most":[135,344],"recently":[136],"proposed":[137],"approaches:":[141],"TCA+":[142],"by":[143,149,154,159,165,242,263,269],"Nam":[144],"et":[145,151,156,161,167],"al.,":[146,152,157,162],"Peters":[147,150,206],"filter":[148],"GP":[153],"Liu":[155],"MO":[158],"Canfora":[160],"CODEP":[164],"Panichella":[166],"al.":[168],"Our":[169],"results":[170,187],"show":[171],"that":[172,248],"HYDRA":[173,215,249,321],"achieves":[174],"an":[175,190],"average":[176,217],"F1-score":[177,252,329],"0.544.":[179],"On":[180],"average,":[181],"across":[182,355],"datasets,":[185],"these":[186],"correspond":[188],"improvement":[191,319],"F1-scores":[194],"26.22":[196],",":[197],"34.99,":[198],"47.43,":[199],"28.61,":[200],"30.14":[202],"percent":[203,221,231,271,277,336],"over":[204,322],"TCA+,":[205],"filter,":[207],"GP,":[208],"MO,":[209],"CODEP,":[211],"respectively.":[212],"addition,":[214],"can":[218,284],"discover":[219],"33":[220],"all":[223,257,293,306],"bugs":[224],"if":[225],"developers":[226,302],"inspect":[227,305],"top":[229,275,334],"20":[230,276,335],"lines":[232,278,337],"code,":[234],"improves":[236,250,267],"best":[238],"baseline":[239,324],"(TCA+)":[241],"44.41":[243],"percent.":[244],"also":[246],"find":[247,311],"Zero-R":[254,268,283],"be":[261,285,298],"5.42":[264],"percent,":[265],"but":[266],"58.65":[270],"when":[272,331],"inspecting":[273,332],"code.":[280],"practice,":[282],"hard":[286],"use":[288],"since":[289],"it":[290],"simply":[291],"predicts":[292],"defective,":[299],"thus":[301],"ones.":[314],"Moreover,":[315],"notice":[317],"terms":[327],"code":[339],"substantial,":[341],"cases":[345],"improvements":[347],"significant":[349],"large":[352],"effect":[353],"sizes":[354],"datasets.":[358]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":38},{"year":2021,"cited_by_count":34},{"year":2020,"cited_by_count":35},{"year":2019,"cited_by_count":51},{"year":2018,"cited_by_count":30},{"year":2017,"cited_by_count":25},{"year":2016,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
