{"id":"https://openalex.org/W4415974814","doi":"https://doi.org/10.1016/j.procs.2025.09.314","title":"Software Defect Prediction Models. A Replication and Extension Study","display_name":"Software Defect Prediction Models. A Replication and Extension Study","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415974814","doi":"https://doi.org/10.1016/j.procs.2025.09.314"},"language":"en","primary_location":{"id":"doi:10.1016/j.procs.2025.09.314","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2025.09.314","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1016/j.procs.2025.09.314","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120285554","display_name":"Nadejde Camelia-Petrina","orcid":null},"institutions":[{"id":"https://openalex.org/I3125347698","display_name":"Babe\u0219-Bolyai University","ror":"https://ror.org/02rmd1t30","country_code":"RO","type":"education","lineage":["https://openalex.org/I3125347698"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Nadejde Camelia-Petrina","raw_affiliation_strings":["Babes-Bolyai University, Department of Computer Science, 1 M. Kog\u0103lniceanu Street, 400084 Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Babes-Bolyai University, Department of Computer Science, 1 M. Kog\u0103lniceanu Street, 400084 Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I3125347698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5120285555","display_name":"Vescan Andreea","orcid":null},"institutions":[{"id":"https://openalex.org/I3125347698","display_name":"Babe\u0219-Bolyai University","ror":"https://ror.org/02rmd1t30","country_code":"RO","type":"education","lineage":["https://openalex.org/I3125347698"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Vescan Andreea","raw_affiliation_strings":["Babes-Bolyai University, Department of Computer Science, 1 M. Kog\u0103lniceanu Street, 400084 Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Babes-Bolyai University, Department of Computer Science, 1 M. Kog\u0103lniceanu Street, 400084 Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I3125347698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5120285555"],"corresponding_institution_ids":["https://openalex.org/I3125347698"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40001263,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"270","issue":null,"first_page":"1936","last_page":"1945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9606999754905701,"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":0.9606999754905701,"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":0.0071000000461936,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.0034000000450760126,"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/support-vector-machine","display_name":"Support vector machine","score":0.7268999814987183},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.692799985408783},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6758999824523926},{"id":"https://openalex.org/keywords/oversampling","display_name":"Oversampling","score":0.6676999926567078},{"id":"https://openalex.org/keywords/replication","display_name":"Replication (statistics)","score":0.5864999890327454},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5817000269889832},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5769000053405762},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.5428000092506409},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5404999852180481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8766000270843506},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7268999814987183},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.692799985408783},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6758999824523926},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.6676999926567078},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6089000105857849},{"id":"https://openalex.org/C12590798","wikidata":"https://www.wikidata.org/wiki/Q3933199","display_name":"Replication (statistics)","level":2,"score":0.5864999890327454},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5817000269889832},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5769000053405762},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.570900022983551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5681999921798706},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5404999852180481},{"id":"https://openalex.org/C1009929","wikidata":"https://www.wikidata.org/wiki/Q179550","display_name":"Software bug","level":3,"score":0.527400016784668},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5170999765396118},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3855000138282776},{"id":"https://openalex.org/C117447612","wikidata":"https://www.wikidata.org/wiki/Q1412670","display_name":"Software quality","level":4,"score":0.3393000066280365},{"id":"https://openalex.org/C149091818","wikidata":"https://www.wikidata.org/wiki/Q2429814","display_name":"Software system","level":3,"score":0.3343999981880188},{"id":"https://openalex.org/C529173508","wikidata":"https://www.wikidata.org/wiki/Q638608","display_name":"Software development","level":3,"score":0.32010000944137573},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.31369999051094055},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31290000677108765},{"id":"https://openalex.org/C82214349","wikidata":"https://www.wikidata.org/wiki/Q657339","display_name":"Software metric","level":5,"score":0.296099990606308},{"id":"https://openalex.org/C180152950","wikidata":"https://www.wikidata.org/wiki/Q2904257","display_name":"Software development process","level":4,"score":0.28450000286102295},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.procs.2025.09.314","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2025.09.314","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.procs.2025.09.314","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2025.09.314","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1985410000","https://openalex.org/W2026750231","https://openalex.org/W2064161267","https://openalex.org/W2097883090","https://openalex.org/W2126626812","https://openalex.org/W2135093973","https://openalex.org/W2167846874","https://openalex.org/W2621582719","https://openalex.org/W2906264889","https://openalex.org/W3009290003","https://openalex.org/W4246635748"],"related_works":[],"abstract_inverted_index":{"Predicting":[0],"software":[1,23,192],"defects":[2],"is":[3,10],"crucial":[4],"for":[5,14,170,179],"ensuring":[6],"reliable":[7],"systems":[8],"and":[9,31,49,77,91,123],"a":[11,44,59,114,177],"critical":[12],"concern":[13],"the":[15,18,41,64,93,119,132,135,141,147,171,180],"industry.":[16],"Automating":[17],"Defect":[19,193],"detection":[20],"process":[21],"in":[22,85,154,161,191],"programs":[24],"can":[25],"significantly":[26],"reduce":[27],"errors,":[28],"development":[29],"time,":[30],"costs.":[32],"This":[33,99,174],"paper":[34,100],"has":[35],"two":[36],"primary":[37],"aims:":[38],"to":[39,50,188],"generalize":[40],"findings":[42],"of":[43,118,121,182],"previous":[45],"study":[46,57,105],"through":[47,54],"replication":[48,65],"provide":[51],"new":[52],"insights":[53],"an":[55,103],"extension":[56,104,148],"using":[58],"different":[60],"prediction":[61],"model.":[62],"For":[63],"study,":[66,149],"three":[67],"methods":[68],"are":[69],"used:":[70],"Naive":[71],"Bayes":[72],"(NB),":[73],"Decision":[74],"Tree":[75],"(DT),":[76],"Random":[78,136],"Forest":[79,137],"(RF)":[80],"algorithm.":[81],"All":[82],"models":[83],"used":[84,89],"this":[86],"research":[87,175],"were":[88],"before":[90],"after":[92],"Hybrid":[94],"Feature":[95],"Selection":[96],"(HFS)":[97],"method.":[98],"also":[101],"provides":[102],"that":[106,112],"incorporates":[107],"Support":[108],"Vector":[109],"Machines":[110],"(SVM)":[111],"allowed":[113],"more":[115],"comprehensive":[116],"understanding":[117],"impact":[120],"HFS":[122],"oversampling":[124],"on":[125],"classifier":[126],"performance.":[127],"The":[128],"replicated":[129],"results":[130],"confirmed":[131],"original":[133],"findings:":[134],"algorithm":[138],"consistently":[139],"achieved":[140],"highest":[142],"accuracy":[143],"across":[144],"datasets.":[145],"In":[146],"SVM":[150,183],"demonstrated":[151],"superior":[152],"performance":[153],"detecting":[155],"minority":[156],"class":[157],"defects,":[158],"as":[159],"reflected":[160],"its":[162],"higher":[163],"Matthew\u2019s":[164],"Correlation":[165],"Coefficient":[166],"(MCC)":[167],"scores,":[168],"particularly":[169],"PC3":[172],"dataset.":[173],"establishes":[176],"foundation":[178],"use":[181],"along":[184],"with":[185],"other":[186],"classifiers":[187],"address":[189],"challenges":[190],"prediction.":[194]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-06T00:00:00"}