{"id":"https://openalex.org/W4224214784","doi":"https://doi.org/10.1145/3511598","title":"An Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement","display_name":"An Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement","publication_year":2022,"publication_date":"2022-04-19","ids":{"openalex":"https://openalex.org/W4224214784","doi":"https://doi.org/10.1145/3511598"},"language":"en","primary_location":{"id":"doi:10.1145/3511598","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511598","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511598","source":{"id":"https://openalex.org/S142627899","display_name":"ACM Transactions on Software Engineering and Methodology","issn_l":"1049-331X","issn":["1049-331X","1557-7392"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Software Engineering and Methodology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3511598","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101406450","display_name":"Qiang Hu","orcid":"https://orcid.org/0000-0002-8251-1669"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":true,"raw_author_name":"Qiang Hu","raw_affiliation_strings":["University of Luxembourg, Luxembourg"],"affiliations":[{"raw_affiliation_string":"University of Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023978917","display_name":"Yuejun Guo","orcid":"https://orcid.org/0000-0002-5535-2420"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Yuejun Guo","raw_affiliation_strings":["University of Luxembourg, Luxembourg"],"affiliations":[{"raw_affiliation_string":"University of Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000695937","display_name":"Maxime Cordy","orcid":"https://orcid.org/0000-0001-8312-1358"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Maxime Cordy","raw_affiliation_strings":["University of Luxembourg, Luxembourg"],"affiliations":[{"raw_affiliation_string":"University of Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084396416","display_name":"Xiaofei Xie","orcid":"https://orcid.org/0000-0002-1288-6502"},"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":"Xiaofei Xie","raw_affiliation_strings":["Singapore Management University, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore Management University, Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101468661","display_name":"Lei Ma","orcid":"https://orcid.org/0000-0002-8621-2420"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Lei Ma","raw_affiliation_strings":["University of Alberta, Canada"],"affiliations":[{"raw_affiliation_string":"University of Alberta, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081145634","display_name":"Mike Papadakis","orcid":"https://orcid.org/0000-0003-1852-2547"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Mike Papadakis","raw_affiliation_strings":["University of Luxembourg, Luxembourg"],"affiliations":[{"raw_affiliation_string":"University of Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040574362","display_name":"Yves Le Traon","orcid":"https://orcid.org/0000-0002-1045-4861"},"institutions":[{"id":"https://openalex.org/I186903577","display_name":"University of Luxembourg","ror":"https://ror.org/036x5ad56","country_code":"LU","type":"education","lineage":["https://openalex.org/I186903577"]}],"countries":["LU"],"is_corresponding":false,"raw_author_name":"Yves Le Traon","raw_affiliation_strings":["University of Luxembourg, Luxembourg"],"affiliations":[{"raw_affiliation_string":"University of Luxembourg, Luxembourg","institution_ids":["https://openalex.org/I186903577"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101406450"],"corresponding_institution_ids":["https://openalex.org/I186903577"],"apc_list":null,"apc_paid":null,"fwci":4.084,"has_fulltext":true,"cited_by_count":40,"citation_normalized_percentile":{"value":0.95128814,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"31","issue":"4","first_page":"1","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9995999932289124,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9977999925613403,"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/retraining","display_name":"Retraining","score":0.8875606060028076},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8183493614196777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6082286834716797},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5885319113731384},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5870484113693237},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.5362868309020996},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5034438967704773},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5028700232505798},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4634658396244049},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44814300537109375},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4471021592617035},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.443574994802475},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43652868270874023},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.43364861607551575},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4278098940849304},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4234582781791687},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41769614815711975},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.41023725271224976},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11932390928268433},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08978584408760071},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0712043046951294}],"concepts":[{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.8875606060028076},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8183493614196777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6082286834716797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5885319113731384},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5870484113693237},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.5362868309020996},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5034438967704773},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5028700232505798},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4634658396244049},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44814300537109375},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4471021592617035},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.443574994802475},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43652868270874023},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.43364861607551575},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4278098940849304},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4234582781791687},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41769614815711975},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.41023725271224976},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11932390928268433},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08978584408760071},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0712043046951294},{"id":"https://openalex.org/C155202549","wikidata":"https://www.wikidata.org/wiki/Q178803","display_name":"International trade","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3511598","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511598","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511598","source":{"id":"https://openalex.org/S142627899","display_name":"ACM Transactions on Software Engineering and Methodology","issn_l":"1049-331X","issn":["1049-331X","1557-7392"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Software Engineering and Methodology","raw_type":"journal-article"},{"id":"pmh:oai:ink.library.smu.edu.sg:sis_research-8198","is_oa":true,"landing_page_url":"https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=8198&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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://doi.org/10.1145/3511598","raw_type":"Journal Article"},{"id":"pmh:oai:orbilu.uni.lu:10993/50265","is_oa":true,"landing_page_url":"http://orbilu.uni.lu/handle/10993/50265","pdf_url":null,"source":{"id":"https://openalex.org/S4306401815","display_name":"Open Repository and Bibliography (University of Luxembourg)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I186903577","host_organization_name":"University of Luxembourg","host_organization_lineage":["https://openalex.org/I186903577"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null}],"best_oa_location":{"id":"doi:10.1145/3511598","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511598","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511598","source":{"id":"https://openalex.org/S142627899","display_name":"ACM Transactions on Software Engineering and Methodology","issn_l":"1049-331X","issn":["1049-331X","1557-7392"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Software Engineering and Methodology","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4224214784.pdf","grobid_xml":"https://content.openalex.org/works/W4224214784.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1493526108","https://openalex.org/W1567301746","https://openalex.org/W1975672287","https://openalex.org/W1995875735","https://openalex.org/W2011674654","https://openalex.org/W2105767494","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2125186487","https://openalex.org/W2140609507","https://openalex.org/W2342840547","https://openalex.org/W2531327146","https://openalex.org/W2533523411","https://openalex.org/W2616028256","https://openalex.org/W2750384547","https://openalex.org/W2804337238","https://openalex.org/W2948254043","https://openalex.org/W2954629067","https://openalex.org/W2963327228","https://openalex.org/W2963913218","https://openalex.org/W2968940383","https://openalex.org/W2970946347","https://openalex.org/W2982316857","https://openalex.org/W2997532515","https://openalex.org/W3000315285","https://openalex.org/W3005940936","https://openalex.org/W3040002795","https://openalex.org/W3041012898","https://openalex.org/W3042703469","https://openalex.org/W3090426403","https://openalex.org/W3091388282","https://openalex.org/W3100925971","https://openalex.org/W3105347387","https://openalex.org/W3112486745","https://openalex.org/W3118608800","https://openalex.org/W3120991880","https://openalex.org/W3124058431","https://openalex.org/W3125205424","https://openalex.org/W3130354627","https://openalex.org/W3134428469","https://openalex.org/W3146834245","https://openalex.org/W3161493619","https://openalex.org/W3205471381","https://openalex.org/W4200630710","https://openalex.org/W4300877800","https://openalex.org/W6680902425","https://openalex.org/W6704559304","https://openalex.org/W6762924995"],"related_works":["https://openalex.org/W4387327236","https://openalex.org/W2183488467","https://openalex.org/W2028462208","https://openalex.org/W4309907966","https://openalex.org/W4387896287","https://openalex.org/W4285337533","https://openalex.org/W2982831492","https://openalex.org/W1990237101","https://openalex.org/W4300172249","https://openalex.org/W2187490799"],"abstract_inverted_index":{"Similar":[0],"to":[1,13,27,41,61,110,185],"traditional":[2],"software":[3],"that":[4,141],"is":[5,38],"constantly":[6],"under":[7,164],"evolution,":[8],"deep":[9,69],"neural":[10,70],"networks":[11,71],"need":[12],"evolve":[14],"upon":[15],"the":[16,46,66,112,115,145,153,158,162,173,180],"rapid":[17],"growth":[18],"of":[19,45,114,157,175],"test":[20,48,135],"data":[21,91,119,149,166],"for":[22,34,192],"continuous":[23],"enhancement":[24,194],"(e.g.,":[25],"adapting":[26],"distribution":[28,92,120,176,199],"shift":[29,200],"in":[30],"a":[31,58,106,132],"new":[32],"environment":[33],"deployment).":[35],"However,":[36],"it":[37],"labor":[39],"intensive":[40],"manually":[42],"label":[43],"all":[44],"collected":[47],"data.":[49,155],"Test":[50],"selection":[51,78,136,159],"solves":[52],"this":[53,101],"problem":[54],"by":[55,183],"strategically":[56],"choosing":[57],"small":[59],"set":[60],"label.":[62],"Via":[63],"retraining":[64,87,116,142],"with":[65],"selected":[67,148,154],"set,":[68],"will":[72],"achieve":[73],"competitive":[74],"accuracy.":[75],"Unfortunately,":[76],"existing":[77],"metrics":[79,160,182],"involve":[80],"three":[81],"main":[82],"limitations:":[83],"(1)":[84],"using":[85,143,151],"different":[86],"processes,":[88],"(2)":[89],"ignoring":[90],"shifts,":[93],"and":[94,118,147,178,188,197],"(3)":[95],"being":[96],"insufficiently":[97],"evaluated.":[98],"To":[99],"fill":[100],"gap,":[102],"we":[103,129],"first":[104],"conduct":[105],"systemically":[107],"empirical":[108],"study":[109],"reveal":[111,140],"impact":[113,174],"process":[117],"on":[121,126,195],"model":[122,193],"enhancement.":[123],"Then":[124],"based":[125],"our":[127],"findings,":[128],"propose":[130],"DAT,":[131],"novel":[133],"distribution-aware":[134],"metric.":[137],"Experimental":[138],"results":[139],"both":[144],"training":[146],"outperforms":[150,179],"only":[152],"None":[156],"perform":[161],"best":[163],"various":[165],"distributions.":[167],"By":[168],"contrast,":[169],"DAT":[170],"effectively":[171],"alleviates":[172],"shifts":[177],"compared":[181],"up":[184],"five":[186],"times":[187],"30.09%":[189],"accuracy":[190],"improvement":[191],"simulated":[196],"in-the-wild":[198],"scenarios,":[201],"respectively.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}