{"id":"https://openalex.org/W7124132178","doi":"https://doi.org/10.1109/icpads67057.2025.11323081","title":"An Enhanced Collaborative Forest Semi-Supervised Software Defect Prediction Method Based on Heterogeneous Integration","display_name":"An Enhanced Collaborative Forest Semi-Supervised Software Defect Prediction Method Based on Heterogeneous Integration","publication_year":2025,"publication_date":"2025-12-14","ids":{"openalex":"https://openalex.org/W7124132178","doi":"https://doi.org/10.1109/icpads67057.2025.11323081"},"language":null,"primary_location":{"id":"doi:10.1109/icpads67057.2025.11323081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5123023801","display_name":"Fanqi Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I121799043","display_name":"Electric Power University","ror":"https://ror.org/01p4b7n26","country_code":"VN","type":"education","lineage":["https://openalex.org/I121799043"]},{"id":"https://openalex.org/I179060312","display_name":"Northeast Electric Power University","ror":"https://ror.org/00zqaxa34","country_code":"CN","type":"education","lineage":["https://openalex.org/I179060312"]}],"countries":["CN","VN"],"is_corresponding":false,"raw_author_name":"Fanqi Meng","raw_affiliation_strings":["School of Computer Science, Northeast Electric Power University,Jilin City,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northeast Electric Power University,Jilin City,China","institution_ids":["https://openalex.org/I121799043","https://openalex.org/I179060312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068603055","display_name":"Huimin Li","orcid":"https://orcid.org/0000-0001-8709-3155"},"institutions":[{"id":"https://openalex.org/I121799043","display_name":"Electric Power University","ror":"https://ror.org/01p4b7n26","country_code":"VN","type":"education","lineage":["https://openalex.org/I121799043"]},{"id":"https://openalex.org/I179060312","display_name":"Northeast Electric Power University","ror":"https://ror.org/00zqaxa34","country_code":"CN","type":"education","lineage":["https://openalex.org/I179060312"]}],"countries":["CN","VN"],"is_corresponding":false,"raw_author_name":"Huimin Li","raw_affiliation_strings":["School of Computer Science, Northeast Electric Power University,Jilin City,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northeast Electric Power University,Jilin City,China","institution_ids":["https://openalex.org/I121799043","https://openalex.org/I179060312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101896849","display_name":"Yongjun Li","orcid":"https://orcid.org/0000-0001-7411-6944"},"institutions":[{"id":"https://openalex.org/I121799043","display_name":"Electric Power University","ror":"https://ror.org/01p4b7n26","country_code":"VN","type":"education","lineage":["https://openalex.org/I121799043"]},{"id":"https://openalex.org/I179060312","display_name":"Northeast Electric Power University","ror":"https://ror.org/00zqaxa34","country_code":"CN","type":"education","lineage":["https://openalex.org/I179060312"]}],"countries":["CN","VN"],"is_corresponding":false,"raw_author_name":"Yongjun Li","raw_affiliation_strings":["School of Computer Science, Northeast Electric Power University,Jilin City,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northeast Electric Power University,Jilin City,China","institution_ids":["https://openalex.org/I121799043","https://openalex.org/I179060312"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9297000169754028,"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":0.9297000169754028,"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":0.008299999870359898,"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/T12423","display_name":"Software Reliability and Analysis Research","score":0.008200000040233135,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.5414000153541565},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.5403000116348267},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5329999923706055},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5232999920845032},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4749999940395355},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.46889999508857727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.654699981212616},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5579000115394592},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.5414000153541565},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.5403000116348267},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5329999923706055},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5232999920845032},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5063999891281128},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49939998984336853},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4749999940395355},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.46889999508857727},{"id":"https://openalex.org/C1009929","wikidata":"https://www.wikidata.org/wiki/Q179550","display_name":"Software bug","level":3,"score":0.42179998755455017},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.36550000309944153},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2630000114440918}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpads67057.2025.11323081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.6191498041152954}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W3008381189","https://openalex.org/W4304688778","https://openalex.org/W4372402741","https://openalex.org/W4406012605"],"related_works":[],"abstract_inverted_index":{"Early-stage":[0],"software":[1],"defect":[2,49],"prediction":[3],"faces":[4],"scarce":[5],"labeled":[6,59,79],"data,":[7],"limiting":[8],"supervised":[9],"learning":[10],"effectiveness.":[11],"Existing":[12],"semi-supervised":[13],"methods":[14,76],"suffer":[15],"from":[16],"low-quality":[17],"pseudolabels":[18],"and":[19,42,68],"CoForest's":[20],"homogeneous":[21],"classifiers":[22,34],"restrict":[23],"pattern":[24],"capture.":[25],"This":[26],"paper":[27],"proposes":[28],"Enhanced":[29],"CoForest":[30],"(ECoForest),":[31],"featuring":[32],"heterogeneous":[33],"for":[35],"sample":[36],"adaptability,":[37],"dynamic":[38],"confidence":[39],"pseudo-label":[40],"selection,":[41],"adaptive":[43],"population":[44],"mechanism.":[45],"Experiments":[46],"on":[47],"eight":[48],"datasets":[50],"show":[51],"ECoForest":[52,72],"achieves":[53],"0.8231":[54],"AUC":[55],"with":[56,65],"only":[57],"20%":[58],"data-":[60],"7.1%":[61],"higher":[62],"than":[63],"CoForest,":[64],"3.3%":[66],"F1-score":[67],"6.9%":[69],"G-mean":[70],"improvements.":[71],"outperforms":[73],"four":[74],"baseline":[75],"under":[77],"limited":[78],"data":[80],"conditions.":[81]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-01-15T00:00:00"}