{"id":"https://openalex.org/W4411450015","doi":"https://doi.org/10.1145/3715788","title":"Improving Graph Learning-Based Fault Localization with Tailored Semi-supervised Learning","display_name":"Improving Graph Learning-Based Fault Localization with Tailored Semi-supervised Learning","publication_year":2025,"publication_date":"2025-06-19","ids":{"openalex":"https://openalex.org/W4411450015","doi":"https://doi.org/10.1145/3715788"},"language":"en","primary_location":{"id":"doi:10.1145/3715788","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3715788","pdf_url":null,"source":{"id":"https://openalex.org/S4404663975","display_name":"Proceedings of the ACM on software engineering.","issn_l":"2994-970X","issn":["2994-970X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Software Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3715788","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100373936","display_name":"Chun Li","orcid":"https://orcid.org/0009-0007-9787-3586"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Li","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0007-9787-3586","affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hui Li","orcid":"https://orcid.org/0009-0006-2646-4251"},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Li","raw_affiliation_strings":["Samsung Electronics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0006-2646-4251","affiliations":[{"raw_affiliation_string":"Samsung Electronics, Nanjing, China","institution_ids":["https://openalex.org/I4210155230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100664779","display_name":"Zhong Li","orcid":"https://orcid.org/0000-0002-3849-3416"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Li","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-3849-3416","affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002720603","display_name":"Minxue Pan","orcid":"https://orcid.org/0000-0002-4011-5350"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minxue Pan","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4011-5350","affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090810072","display_name":"Xuandong Li","orcid":"https://orcid.org/0000-0003-3090-9568"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuandong Li","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-3090-9568","affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0267,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87340667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"2","issue":"FSE","first_page":"1522","last_page":"1544"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.996399998664856,"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":0.996399998664856,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.988099992275238,"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/T12127","display_name":"Software System Performance and Reliability","score":0.988099992275238,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7441798448562622},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6968692541122437},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6910412311553955},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.661391019821167},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6076745390892029},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.6061681509017944},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.5022826194763184},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4319028854370117},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3489716053009033},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.09787198901176453}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7441798448562622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6968692541122437},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6910412311553955},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.661391019821167},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6076745390892029},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.6061681509017944},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.5022826194763184},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4319028854370117},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3489716053009033},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.09787198901176453}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3715788","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3715788","pdf_url":null,"source":{"id":"https://openalex.org/S4404663975","display_name":"Proceedings of the ACM on software engineering.","issn_l":"2994-970X","issn":["2994-970X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Software Engineering","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3715788","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3715788","pdf_url":null,"source":{"id":"https://openalex.org/S4404663975","display_name":"Proceedings of the ACM on software engineering.","issn_l":"2994-970X","issn":["2994-970X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Software Engineering","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W398859631","https://openalex.org/W1814500939","https://openalex.org/W1857789879","https://openalex.org/W2033644368","https://openalex.org/W2059471177","https://openalex.org/W2070249305","https://openalex.org/W2085443648","https://openalex.org/W2092239677","https://openalex.org/W2101210369","https://openalex.org/W2111316763","https://openalex.org/W2111678864","https://openalex.org/W2343875716","https://openalex.org/W2366278923","https://openalex.org/W2465098971","https://openalex.org/W2550999023","https://openalex.org/W2736091366","https://openalex.org/W2747329762","https://openalex.org/W2762786131","https://openalex.org/W2907492528","https://openalex.org/W2921022558","https://openalex.org/W2958754741","https://openalex.org/W2962715466","https://openalex.org/W2964159205","https://openalex.org/W2984353870","https://openalex.org/W2997591727","https://openalex.org/W3035160371","https://openalex.org/W3035739162","https://openalex.org/W3036014566","https://openalex.org/W3091002423","https://openalex.org/W3095746859","https://openalex.org/W3110943671","https://openalex.org/W3113757710","https://openalex.org/W3154503084","https://openalex.org/W3160492491","https://openalex.org/W3161071537","https://openalex.org/W3195442242","https://openalex.org/W4210831819","https://openalex.org/W4221150228","https://openalex.org/W4225837752","https://openalex.org/W4248855359","https://openalex.org/W4284670965","https://openalex.org/W4284702776","https://openalex.org/W4299828299","https://openalex.org/W4308641610","https://openalex.org/W4312357822","https://openalex.org/W4313563632","https://openalex.org/W4318348348","https://openalex.org/W4366816011","https://openalex.org/W4387360068","https://openalex.org/W4389544322","https://openalex.org/W4392843850","https://openalex.org/W4400582478","https://openalex.org/W4411552782"],"related_works":["https://openalex.org/W4312414840","https://openalex.org/W2794908468","https://openalex.org/W4206276646","https://openalex.org/W1571801203","https://openalex.org/W101422005","https://openalex.org/W192740413","https://openalex.org/W3004135598","https://openalex.org/W2952937263","https://openalex.org/W2131153761","https://openalex.org/W4283732260"],"abstract_inverted_index":{"Due":[0],"to":[1,50,60,81,100,126,145,164,183],"advancements":[2],"in":[3,152,194,214],"graph":[4,7],"neural":[5],"networks,":[6],"learning-based":[8],"fault":[9,52,119,188],"localization":[10,189],"(GBFL)":[11],"methods":[12,20,113,213],"have":[13],"achieved":[14],"promising":[15],"results.":[16],"However,":[17,110],"as":[18,111],"these":[19,112],"are":[21,114],"supervised":[22,86],"learning":[23,27,90],"paradigms":[24],"and":[25,57,105,147,155,175,190],"deep":[26],"is":[28,42,48,55],"typically":[29],"data-hungry,":[30],"they":[31],"can":[32,69,178],"only":[33,61],"be":[34,70],"trained":[35],"on":[36,171],"fully":[37],"labeled":[38,71],"large-scale":[39],"datasets.":[40],"This":[41],"impractical":[43],"because":[44],"labeling":[45,77,108],"failed":[46,66],"tests":[47,67],"similar":[49],"manual":[51],"localization,":[53,120],"which":[54],"time-consuming":[56],"labor-intensive,":[58],"leading":[59],"a":[62,102,133],"small":[63],"portion":[64],"of":[65,85,96,161,187],"that":[68],"within":[72],"limited":[73],"budgets.":[74],"These":[75],"data":[76,99,107,182,195],"limitations":[78],"would":[79],"lead":[80,125],"the":[82,142,158,169,180,185,192,212],"sub-optimal":[83,127],"effectiveness":[84,186],"GBFL":[87,136],"techniques.":[88],"Semi-supervised":[89],"(SSL)":[91],"provides":[92],"an":[93],"effective":[94],"means":[95],"leveraging":[97],"unlabeled":[98,153,162,173,181],"improve":[101,184],"model's":[103],"performance":[104,208],"address":[106,191],"limitations.":[109],"not":[115],"specifically":[116],"designed":[117],"for":[118],"directly":[121],"utilizing":[122],"them":[123],"might":[124],"effectiveness.":[128],"In":[129],"response,":[130],"we":[131],"propose":[132],"novel":[134],"semi-supervised":[135],"framework,":[137],"LEGATO.":[138],"LEGATO":[139,177,205],"first":[140],"leverages":[141],"attention":[143],"mechanism":[144],"identify":[146],"augment":[148],"likely":[149],"fault-unrelated":[150],"sub-graphs":[151],"graphs":[154,163,174],"then":[156],"quantifies":[157],"suspiciousness":[159],"distribution":[160],"estimate":[165],"pseudo-labels.":[166],"Through":[167],"training":[168],"model":[170],"augmented":[172],"pseudo-labels,":[176],"utilize":[179],"restrictions":[193],"labeling.":[196],"By":[197],"extensive":[198],"evaluations":[199],"against":[200],"3":[201],"baselines":[202],"SSL":[203],"methods,":[204],"demonstrates":[206],"superior":[207],"by":[209],"outperforming":[210],"all":[211],"comparison.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}