{"id":"https://openalex.org/W2753740864","doi":"https://doi.org/10.1145/3128473.3128474","title":"A Strategy for Functional Defect Prediction in Homogenous Datasets","display_name":"A Strategy for Functional Defect Prediction in Homogenous Datasets","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2753740864","doi":"https://doi.org/10.1145/3128473.3128474","mag":"2753740864"},"language":"en","primary_location":{"id":"doi:10.1145/3128473.3128474","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3128473.3128474","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Brazilian Symposium on Systematic and Automated Software Testing","raw_type":"proceedings-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/A5037099907","display_name":"Aline Santos de Pontes","orcid":"https://orcid.org/0000-0001-6508-889X"},"institutions":[{"id":"https://openalex.org/I169045520","display_name":"Universidade Federal da Para\u00edba","ror":"https://ror.org/00p9vpz11","country_code":"BR","type":"education","lineage":["https://openalex.org/I169045520"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"A. Pontes","raw_affiliation_strings":["Universidade Federal da Para\u00edba, Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal da Para\u00edba, Brazil","institution_ids":["https://openalex.org/I169045520"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073203752","display_name":"Clauirton Siebra","orcid":"https://orcid.org/0000-0002-9742-2175"},"institutions":[{"id":"https://openalex.org/I169045520","display_name":"Universidade Federal da Para\u00edba","ror":"https://ror.org/00p9vpz11","country_code":"BR","type":"education","lineage":["https://openalex.org/I169045520"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"C. Siebra","raw_affiliation_strings":["Universidade Federal da Para\u00edba, Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal da Para\u00edba, Brazil","institution_ids":["https://openalex.org/I169045520"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057017117","display_name":"Marciele M. Bittencourt","orcid":null},"institutions":[{"id":"https://openalex.org/I169045520","display_name":"Universidade Federal da Para\u00edba","ror":"https://ror.org/00p9vpz11","country_code":"BR","type":"education","lineage":["https://openalex.org/I169045520"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"M. Bittencourt","raw_affiliation_strings":["Universidade Federal da Para\u00edba, Brazil"],"affiliations":[{"raw_affiliation_string":"Universidade Federal da Para\u00edba, Brazil","institution_ids":["https://openalex.org/I169045520"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037099907"],"corresponding_institution_ids":["https://openalex.org/I169045520"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.16019311,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994000196456909,"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":0.9991999864578247,"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/overfitting","display_name":"Overfitting","score":0.9008431434631348},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7566921710968018},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6682382225990295},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.553623616695404},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4776836037635803},{"id":"https://openalex.org/keywords/software-bug","display_name":"Software bug","score":0.47305384278297424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4636678695678711},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.45771732926368713},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.21649399399757385},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10240098834037781}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.9008431434631348},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7566921710968018},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6682382225990295},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.553623616695404},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4776836037635803},{"id":"https://openalex.org/C1009929","wikidata":"https://www.wikidata.org/wiki/Q179550","display_name":"Software bug","level":3,"score":0.47305384278297424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4636678695678711},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.45771732926368713},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.21649399399757385},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10240098834037781},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3128473.3128474","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3128473.3128474","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Brazilian Symposium on Systematic and Automated Software Testing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1573396645","https://openalex.org/W1758508974","https://openalex.org/W1965819307","https://openalex.org/W1978859404","https://openalex.org/W1989936702","https://openalex.org/W1999785511","https://openalex.org/W2045321086","https://openalex.org/W2045651560","https://openalex.org/W2051978688","https://openalex.org/W2052229651","https://openalex.org/W2059405626","https://openalex.org/W2063725206","https://openalex.org/W2072785870","https://openalex.org/W2082315183","https://openalex.org/W2099919734","https://openalex.org/W2104525970","https://openalex.org/W2110122092","https://openalex.org/W2114869486","https://openalex.org/W2143712427","https://openalex.org/W2146136779","https://openalex.org/W2183895070","https://openalex.org/W2186956392","https://openalex.org/W2187291489","https://openalex.org/W2508153212","https://openalex.org/W3105524585","https://openalex.org/W7052736640"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W2989932438","https://openalex.org/W4387297750","https://openalex.org/W2186333919"],"abstract_inverted_index":{"The":[0,51,89,114,138],"optimization":[1,19],"of":[2,14,26,57,74,82,91,116,120,143,174],"test":[3,12,176],"sequences":[4],"is":[5,94,123,132,150],"an":[6],"important":[7],"resource":[8],"to":[9,33,40,79,95,105,152],"improve":[10],"the":[11,80,83,154,164,172],"efficiency":[13],"complex":[15,125],"software":[16],"systems.":[17],"This":[18],"can":[20,47],"be":[21,48],"carried":[22],"out":[23],"by":[24],"means":[25],"defect":[27,63,107,158],"prediction":[28,108],"techniques,":[29],"which":[30,131,160],"are":[31,76,87],"able":[32,151],"identify":[34,153],"modules":[35,46],"with":[36,59],"a":[37,68,97,124],"higher":[38],"chance":[39],"present":[41,67],"problems,":[42],"so":[43],"that":[44,86,147],"these":[45],"first":[49],"evaluated.":[50],"current":[52],"literature":[53],"brings":[54],"some":[55],"proposals":[56],"algorithms":[58],"high":[60],"accuracy":[61],"for":[62,118,127,157],"prediction.":[64],"However":[65],"they":[66],"poor":[69],"generalization":[70],"power,":[71],"since":[72],"problems":[73],"overfitting":[75],"hidden":[77],"due":[78],"nature":[81],"evaluation":[84,119],"methods":[85],"used.":[88],"aim":[90],"this":[92,144,170],"work":[93],"propose":[96],"modelling":[98],"strategy":[99],"based":[100],"on":[101],"more":[102],"homogeneous":[103],"datasets":[104],"trainee":[106],"models":[109],"aimed":[110],"at":[111],"functional":[112],"bugs.":[113],"object":[115],"study":[117],"our":[121,148],"proposal":[122,149],"system":[126,145],"academic":[128],"management":[129],"(SIGAA),":[130],"used":[133],"in":[134,140,161,169],"several":[135],"Brazilian":[136],"universities.":[137],"application":[139],"successive":[141],"versions":[142],"shows":[146],"best":[155],"approach":[156],"prediction,":[159],"fact":[162],"indicates":[163],"most":[165],"problematic":[166],"modules,":[167],"supporting":[168],"way":[171],"construction":[173],"optimal":[175],"sequences.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}